Landsat 8 Operational Land Imager (OLI)_Thermal Infared Sensor (TIRS) V1

Data.gov (United States)

National Aeronautics and Space Administration — Abstract:The Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) are instruments onboard the Landsat 8 satellite, which was launched in February of...

TIRCIS: A Thermal Infrared, Compact Imaging Spectrometer for Small Satellite Applications

Data.gov (United States)

National Aeronautics and Space Administration — This project will demonstrate how hyperspectral thermal infrared (TIR; 8-14 microns) image data, with a spectral resolution of up to 8 wavenumbers, can be acquired...

A Thermal Imaging Instrument with Uncooled Detectors

Science.gov (United States)

Joseph, A. T.; Barrentine, E. M.; Brown, A. D.

2017-12-01

In this work, we perform an instrument concept study for sustainable thermal imaging over land with uncooled detectors. The National Research Council's Committee on Implementation of a Sustained Land Imaging Program has identified the inclusion of a thermal imager as critical for both current and future land imaging missions. Such an imaging instrument operating in two bands located at approximately 11 and 12 microns (for example, in Landsat 8, and also Landsat 9 when launched) will provide essential information for furthering our hydrologic understanding at scales of human influence, and produce field-scale moisture information through accurate retrievals of evapotranspiration (ET). Landsat 9 is slated to recycle the TIRS-2 instrument launched with Landsat 8 that uses cooled quantum well infrared photodetectors (QWIPs), hence requiring expensive and massive cryocooler technology to achieve its required spectral and spatial accuracies. Our goal is to conceptualize and develop a thermal imaging instrument which leverages recent and imminent technology advances in uncooled detectors. Such detector technology will offer the benefit of greatly reduced instrument cost, mass, and power at the expense of some acceptable loss in detector sensitivity. It would also allow a thermal imaging instrument to be fielded on board a low-cost platform, e.g., a CubeSat. Sustained and enhanced land imaging is crucial for providing high-quality science data on change in land use, forest health, crop status, environment, and climate. Accurate satellite mapping of ET at the agricultural field scale (the finest spatial scale of the environmental processes of interest) requires high-quality thermal data to produce the corresponding accurate land surface temperature (LST) retrievals used to drive an ET model. Such an imaging instrument would provide important information on the following: 1) the relationship between land-use and land/water management practices and water use dynamics; 2) the

Deep Space Thermal Cycle Testing of Advanced X-Ray Astrophysics Facility - Imaging (AXAF-I) Solar Array Panels Test

National Research Council Canada - National Science Library

Sisco, Jimmy

1997-01-01

The NASA Advanced X-ray Astrophysics Facility - Imaging (AXAF-I) satellite will be exposed to thermal conditions beyond normal experience flight temperatures due to the satellite's high elliptical orbital flight...

Egypt satellite images for land surface characterization

DEFF Research Database (Denmark)

Hasager, Charlotte Bay

images used for mapping the vegetation cover types and other land cover types in Egypt. The mapping ranges from 1 km resolution to 30 m resolution. The aim is to provide satellite image mapping with land surface characteristics relevant for roughness mapping.......Satellite images provide information on the land surface properties. From optical remote sensing images in the blue, green, red and near-infrared part of the electromagnetic spectrum it is possible to identify a large number of surface features. The report briefly describes different satellite...

Monitoring volcanic thermal activity by Robust Satellite Techniques: achievements and perspectives

Science.gov (United States)

Tramutoli, V.; Marchese, F.; Mazzeo, G.; Pergola, N.

2009-12-01

Satellite data have been increasingly used in last decades to study active volcanoes and to monitor thermal activity variation in space-time domain. Several satellite techniques and original methods have been developed and tested, devoted to hotspot detection and thermal monitoring. Among them, a multi-temporal approach, named RST (Robust Satellite Techniques), has shown high performances in detecting hotspots, with a low false positive rate under different observational and atmospheric conditions, providing also a potential toward low-level thermal anomalies which may announce incoming eruptions. As the RST scheme is intrinsically exportable on different geographic areas and satellite sensors, it has been applied and tested on a number of volcanoes and in different environmental conditions. This work presents major results and outcomes of studies carried out on Etna and Stromboli (Italy), Merapi (Java Indonesia), Asamayama (Japan), Jebel Al Tair (Yemen) by using different satellite systems and sensors (e.g. NOAA-AVHRR, EOS-MODIS, MSG-SEVIRI). Performances on hotspot detection, early warning and real-time monitoring, together with capabilities in possible thermal precursor identification, will be presented and discussed.

Technical and cost advantages of silicon carbide telescopes for small-satellite imaging applications

Science.gov (United States)

Kasunic, Keith J.; Aikens, Dave; Szwabowski, Dean; Ragan, Chip; Tinker, Flemming

2017-09-01

Small satellites ("SmallSats") are a growing segment of the Earth imaging and remote sensing market. Designed to be relatively low cost and with performance tailored to specific end-use applications, they are driving changes in optical telescope assembly (OTA) requirements. OTAs implemented in silicon carbide (SiC) provide performance advantages for space applications but have been predominately limited to large programs. A new generation of lightweight and thermally-stable designs is becoming commercially available, expanding the application of SiC to small satellites. This paper reviews the cost and technical advantages of an OTA designed using SiC for small satellite platforms. Taking into account faceplate fabrication quilting and surface distortion after gravity release, an optimized open-back SiC design with a lightweighting of 70% for a 125-mm SmallSat-class primary mirror has an estimated mass area density of 2.8 kg/m2 and an aspect ratio of 40:1. In addition, the thermally-induced surface error of such optimized designs is estimated at λ/150 RMS per watt of absorbed power. Cost advantages of SiC include reductions in launch mass, thermal-management infrastructure, and manufacturing time based on allowable assembly tolerances.

Satellite images to aircraft in flight. [GEOS image transmission feasibility analysis

Science.gov (United States)

Camp, D.; Luers, J. K.; Kadlec, P. W.

1977-01-01

A study has been initiated to evaluate the feasibility of transmitting selected GOES images to aircraft in flight. Pertinent observations that could be made from satellite images on board aircraft include jet stream activity, cloud/wind motion, cloud temperatures, tropical storm activity, and location of severe weather. The basic features of the Satellite Aircraft Flight Environment System (SAFES) are described. This system uses East GOES and West GOES satellite images, which are interpreted, enhanced, and then retransmitted to designated aircraft.

Multi sensor satellite imagers for commercial remote sensing

Science.gov (United States)

Cronje, T.; Burger, H.; Du Plessis, J.; Du Toit, J. F.; Marais, L.; Strumpfer, F.

2005-10-01

This paper will discuss and compare recent refractive and catodioptric imager designs developed and manufactured at SunSpace for Multi Sensor Satellite Imagers with Panchromatic, Multi-spectral, Area and Hyperspectral sensors on a single Focal Plane Array (FPA). These satellite optical systems were designed with applications to monitor food supplies, crop yield and disaster monitoring in mind. The aim of these imagers is to achieve medium to high resolution (2.5m to 15m) spatial sampling, wide swaths (up to 45km) and noise equivalent reflectance (NER) values of less than 0.5%. State-of-the-art FPA designs are discussed and address the choice of detectors to achieve these performances. Special attention is given to thermal robustness and compactness, the use of folding prisms to place multiple detectors in a large FPA and a specially developed process to customize the spectral selection with the need to minimize mass, power and cost. A refractive imager with up to 6 spectral bands (6.25m GSD) and a catodioptric imager with panchromatic (2.7m GSD), multi-spectral (6 bands, 4.6m GSD), hyperspectral (400nm to 2.35μm, 200 bands, 15m GSD) sensors on the same FPA will be discussed. Both of these imagers are also equipped with real time video view finding capabilities. The electronic units could be subdivided into the Front-End Electronics and Control Electronics with analogue and digital signal processing. A dedicated Analogue Front-End is used for Correlated Double Sampling (CDS), black level correction, variable gain and up to 12-bit digitizing and high speed LVDS data link to a mass memory unit.

Automatic Cloud and Shadow Detection in Optical Satellite Imagery Without Using Thermal Bands—Application to Suomi NPP VIIRS Images over Fennoscandia

Directory of Open Access Journals (Sweden)

Eija Parmes

2017-08-01

Full Text Available In land monitoring applications, clouds and shadows are considered noise that should be removed as automatically and quickly as possible, before further analysis. This paper presents a method to detect clouds and shadows in Suomi NPP satellite’s VIIRS (Visible Infrared Imaging Radiometer Suite satellite images. The proposed cloud and shadow detection method has two distinct features when compared to many other methods. First, the method does not use the thermal bands and can thus be applied to other sensors which do not contain thermal channels, such as Sentinel-2 data. Secondly, the method uses the ratio between blue and green reflectance to detect shadows. Seven hundred and forty-seven VIIRS images over Fennoscandia from August 2014 to April 2016 were processed to train and develop the method. Twenty four points from every tenth of the images were used in accuracy assessment. These 1752 points were interpreted visually to cloud, cloud shadow and clear classes, then compared to the output of the cloud and shadow detection. The comparison on VIIRS images showed 94.2% correct detection rates and 11.1% false alarms for clouds, and respectively 36.1% and 82.7% for shadows. The results on cloud detection were similar to state-of-the-art methods. Shadows showed correctly on the northern edge of the clouds, but many shadows were wrongly assigned to other classes in some cases (e.g., to water class on lake and forest boundary, or with shadows over cloud. This may be due to the low spatial resolution of VIIRS images, where shadows are only a few pixels wide and contain lots of mixed pixels.

Thermal imbalance force modelling for a GPS satellite using the finite element method

Science.gov (United States)

Vigue, Yvonne; Schutz, Bob E.

1991-01-01

Methods of analyzing the perturbation due to thermal radiation and determining its effects on the orbits of GPS satellites are presented, with emphasis on the FEM technique to calculate satellite solar panel temperatures which are used to determine the magnitude and direction of the thermal imbalance force. Although this force may not be responsible for all of the force mismodeling, conditions may work in combination with the thermal imbalance force to produce such accelerations on the order of 1.e-9 m/sq s. If submeter accurate orbits and centimeter-level accuracy for geophysical applications are desired, a time-dependent model of the thermal imbalance force should be used, especially when satellites are eclipsing, where the observed errors are larger than for satellites in noneclipsing orbits.

STUDY ON SHADOW EFFECTS OF VARIOUS FEATURES ON CLOSE RANGE THERMAL IMAGES

Directory of Open Access Journals (Sweden)

C. L. Liao

2012-07-01

Full Text Available Thermal infrared data become more popular in remote sensing investigation, for it could be acquired both in day and night. The change of temperature has special characteristic in natural environment, so the thermal infrared images could be used in monitoring volcanic landform, the urban development, and disaster prevention. Heat shadow is formed by reflecting radiating capacity which followed the objects. Because of poor spatial resolution of thermal infrared images in satellite sensor, shadow effects were usually ignored. This research focus on discussing the shadow effects of various features, which include metals and nonmetallic materials. An area-based thermal sensor, FLIR-T360 was selected to acquire thermal images. Various features with different emissivity were chosen as reflective surface to obtain thermal shadow in normal atmospheric temperature. Experiments found that the shadow effects depend on the distance between sensors and features, depression angle, object temperature and emissivity of reflective surface. The causes of shadow effects have been altered in the experiment for analyzing the variance in thermal infrared images. The result shows that there were quite different impacts by shadow effects between metals and nonmetallic materials. The further research would be produced a math model to describe the shadow effects of different features in the future work.

Phenomena of non-thermal electrons from the X-ray imaging crystal spectrometer on J-TEXT tokamak

International Nuclear Information System (INIS)

Yan, W.; Chen, Z.Y.; Jin, W.; Huang, D.W.; Lee, S.G.; Shi, Y.J.; Tong, R.H.; Wang, S.Y.; Wei, Y.N.; Ma, T.K.; Zhuang, G.

2016-01-01

Highlights: • Some lines from X-ray imaging crystal spectrometer (XICS) can be enhanced by non-thermal electrons, such as q, r satellite lines and z lines. • Analyze the non-thermal phenomena can reduce the error of electron temperature deduced from the intensity ratio of different lines of the He-like argon spectra from XICS. • XICS can be a tool to measure the non-thermal phenomena from these enhanced lines. - Abstract: A high spectra resolution X-ray imaging crystal spectrometer has been implemented on J-TEXT Tokamak for the measurements of K_α spectra of helium-like argon and its satellite lines. The wavelength range of K_α spectra of helium-like argon is from 3.9494 Å to 3.9944 Å that includes the resonance line w, intercombination lines x and y, forbidden line z and numerous satellite lines, referenced using standard Gabriel notation. In low-density discharge, the intensity of q, r satellite lines and z lines can be significantly enhanced by non-thermal electrons. Non-thermal electrons are produced due to the low plasma density. The high hard X-ray flux from NaI detector and significant downshift electron cyclotron emissions from energetic runaway electrons also indicated that there is a large population of runaway electrons in the low-density discharge. The non-thermal part of electrons can affect the excitation/transition equilibrium or ionization/recombination equilibrium. The q line is mainly produced by inner-shell excitation of lithium-like argon, and the r line is partially produced by inner-shell excitation of lithium-like argon and dielectronic recombination of helium-like argon.

Phenomena of non-thermal electrons from the X-ray imaging crystal spectrometer on J-TEXT tokamak

Energy Technology Data Exchange (ETDEWEB)

Yan, W. [State Key Laboratory of Advanced Electromagnetic Engineering and Technology, School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan (China); Chen, Z.Y., E-mail: zychen@hust.edu.cn [State Key Laboratory of Advanced Electromagnetic Engineering and Technology, School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan (China); Jin, W. [Center of Interface Dynamics for Sustainability, China Academy of Engineering Physics, Chengdu 610200, Sichuan (China); Huang, D.W. [State Key Laboratory of Advanced Electromagnetic Engineering and Technology, School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan (China); Lee, S.G.; Shi, Y.J. [National Fusion Research Institute, Daejeon 305-333 (Korea, Republic of); Tong, R.H.; Wang, S.Y.; Wei, Y.N.; Ma, T.K.; Zhuang, G. [State Key Laboratory of Advanced Electromagnetic Engineering and Technology, School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan (China)

2016-11-01

Highlights: • Some lines from X-ray imaging crystal spectrometer (XICS) can be enhanced by non-thermal electrons, such as q, r satellite lines and z lines. • Analyze the non-thermal phenomena can reduce the error of electron temperature deduced from the intensity ratio of different lines of the He-like argon spectra from XICS. • XICS can be a tool to measure the non-thermal phenomena from these enhanced lines. - Abstract: A high spectra resolution X-ray imaging crystal spectrometer has been implemented on J-TEXT Tokamak for the measurements of K{sub α} spectra of helium-like argon and its satellite lines. The wavelength range of K{sub α} spectra of helium-like argon is from 3.9494 Å to 3.9944 Å that includes the resonance line w, intercombination lines x and y, forbidden line z and numerous satellite lines, referenced using standard Gabriel notation. In low-density discharge, the intensity of q, r satellite lines and z lines can be significantly enhanced by non-thermal electrons. Non-thermal electrons are produced due to the low plasma density. The high hard X-ray flux from NaI detector and significant downshift electron cyclotron emissions from energetic runaway electrons also indicated that there is a large population of runaway electrons in the low-density discharge. The non-thermal part of electrons can affect the excitation/transition equilibrium or ionization/recombination equilibrium. The q line is mainly produced by inner-shell excitation of lithium-like argon, and the r line is partially produced by inner-shell excitation of lithium-like argon and dielectronic recombination of helium-like argon.

Virtual Satellite Construction and Application for Image Classification

International Nuclear Information System (INIS)

Su, W G; Su, F Z; Zhou, C H

2014-01-01

Nowadays, most remote sensing image classification uses single satellite remote sensing data, so the number of bands and band spectral width is consistent. In addition, observed phenomenon such as land cover have the same spectral signature, which causes the classification accuracy to decrease as different data have unique characteristic. Therefore, this paper analyzes different optical remote sensing satellites, comparing the spectral differences and proposes the ideas and methods to build a virtual satellite. This article illustrates the research on the TM, HJ-1 and MODIS data. We obtained the virtual band X 0 through these satellites' bands combined it with the 4 bands of a TM image to build a virtual satellite with five bands. Based on this, we used these data for image classification. The experimental results showed that the virtual satellite classification results of building land and water information were superior to the HJ-1 and TM data respectively

New and Emerging Satellite Imaging Capabilities in Support of Safeguards

International Nuclear Information System (INIS)

Johnson, M.; Paquette, J.P.; Spyropoulos, N.; Rainville, L.; Schichor, P.; Hong, M.

2015-01-01

This abstract is focused on new and emerging commercial satellite imagery (CSI) capabilities. For more than a decade, experienced imagery analysts have been exploiting and analyzing CSI in support of the Department of Safeguards. As the remote sensing industry continues to evolve, additional CSI imagery types are becoming available that could enhance our ability to evaluate and verify States' declarations and to investigate the possible presence of undeclared activities. A newly available and promising CSI capability that may have a Safeguards application is Full Motion Video (FMV) imagery collection from satellites. For quite some time, FMV imagery has been collected from airborne platforms, but now FMV sensors are being deployed into space. Like its airborne counterpart, satellite FMV imagery could provide analysts with a great deal of information, including insight into the operational status of facilities and patterns of activity. From a Safeguards perspective, FMV imagery could help the Agency in the evaluation and verification of States' declared facilities and activities. There are advantages of FMV imaging capabilities that cannot be duplicated with other CSI capabilities, including the ability to loiter over areas of interest and the potential to revisit sites multiple times per day. Additional sensor capabilities applicable to the Safeguards mission include, but are not limited to, the following sensors: · Thermal Infrared imaging sensors will be launched in late 2014 to monitor operational status, e.g., heat from a transformer. · High resolution ShortWave Infrared sensors able to characterize materials that could support verification of Additional Protocol declarations under Article 2.a(v). · Unmanned Aerial Vehicles with individual sensors or specific sensor combinations. The Safeguards Symposium provides a forum to showcase and demonstrate safeguards applications for these emerging satellite imaging capabilities. (author)

Thermal imaging in medicine

Directory of Open Access Journals (Sweden)

Jaka Ogorevc

2015-12-01

Full Text Available AbstractIntroduction: Body temperature monitoring is one of the oldest and still one of the most basic diagnostic methods in medicine. In recent years thermal imaging has been increasingly used in measurements of body temperature for diagnostic purposes. Thermal imaging is non-invasive, non-contact method for measuring surface body temperature. Method is quick, painless and patient is not exposed to ionizing radiation or any other body burden.Application of thermal imaging in medicine: Pathological conditions can be indicated as hyper- or hypothermic patterns in many cases. Thermal imaging is presented as a diagnostic method, which can detect such thermal anomalies. This article provides an overview of the thermal imaging applications in various fields of medicine. Thermal imaging has proven to be a suitable method for human febrile temperature screening, for the detection of sites of fractures and infections, a reliable diagnostic tool in the detection of breast cancer and determining the type of skin cancer tumour. It is useful in monitoring the course of a therapy after spinal cord injury, in the detection of food allergies and detecting complications at hemodialysis and is also very effective at the course of treatment of breast reconstruction after mastectomy. With thermal imaging is possible to determine the degrees of burns and early detection of osteomyelitis in diabetic foot phenomenon. The most common and the oldest application of thermal imaging in medicine is the field of rheumatology.Recommendations for use and standards: Essential performance of a thermal imaging camera, measurement method, preparation of a patient and environmental conditions are very important for proper interpretation of measurement results in medical applications of thermal imaging. Standard for screening thermographs was formed for the human febrile temperature screening application.Conclusion: Based on presented examples it is shown that thermal imaging can

Inserts thermal coupling analysis in hexagonal honeycomb plates used for satellite structural design

International Nuclear Information System (INIS)

Boudjemai, A.; Mankour, A.; Salem, H.; Amri, R.; Hocine, R.; Chouchaoui, B.

2014-01-01

Mechanical joints and fasteners are essential elements in joining structural components in mechanical systems. The thermal coupling effect between the adjacent inserts depends to a great extent on the thermal properties of the inserts and the clearance. In this paper the Finite-Element Method (FEM) has been employed to study the insert thermal coupling behaviour of the hexagonal honeycomb panel. Fully coupled thermal analysis was conducted in order to predict thermal coupling phenomena caused by the adjacent inserts under extreme thermal loading conditions. Detailed finite elements models for a honeycomb panel are developed in this study including the insert joints. New approach of the adhesive joint is modelled. Thermal simulations showed that the adjacent inserts cause thermal interference and the adjacent inserts are highly sensitive to the effect of high temperatures. The clearance and thermal interference between the adjacent inserts have an important influence on the satellite equipments (such as the electronics box), which can cause the satellite equipments failures. The results of the model presented in this analysis are significant in the preliminary satellites structural dimensioning which present an effective approach of development by reducing the cost and the time of analysis. - Highlights: •In this work we perform thermal analysis of honeycomb plates using finite element method. •Detailed finite elements models for honeycomb panel are developed in this study including the insert joints. •New approach of the adhesive joint is modelled. •The adjacent inserts cause the thermal interference. •We conclude that this work will help in the analysis and the design of complex satellite structures

New flexible thermal control material for long-life satellite

International Nuclear Information System (INIS)

Sasaki, Shigekuni; Hasuda, Yoshinori; Ichino, Toshihiro

1986-01-01

Flexible thermal control materials are light weight, cheap and excellent in the practical applicability, and are expected to be applied to future long life, large capacity satellites. However, the flexible thermal control materials used at present have the defect that either the space environment withstanding capability or the thermal control performance is poor. Therefore, the authors examined the flexible thermal control materials which are excellent in both these properties, and have developed the thermal control material PEI-OSR using polyether imide films as the substrate. In this study, while comparing with the FEP Teflon with silver vapor deposition, which has been used so far for short life satellites, the long term reliability of the PEI-OSR supposing the use for seven years was examined. As the results, the FEP Teflon with silver vapor deposition caused cracking and separation by irradiation and heat cycle test, and became unusable, but the PEI-OSR did not change its flexibility at all. Also the thermal control performance of the PEI-OSR after the test equivalent to seven years was superior to the initial performance of the Kaptone with aluminum vapor deposition, which has excellent space environment endurance, thus it was clarified that the PEI-OSR is the most excellent for this purpose. (Kako, I.)

Spectrally Consistent Satellite Image Fusion with Improved Image Priors

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg; Aanæs, Henrik; Jensen, Thomas B.S.

2006-01-01

Here an improvement to our previous framework for satellite image fusion is presented. A framework purely based on the sensor physics and on prior assumptions on the fused image. The contributions of this paper are two fold. Firstly, a method for ensuring 100% spectrally consistency is proposed......, even when more sophisticated image priors are applied. Secondly, a better image prior is introduced, via data-dependent image smoothing....

Thermal Analysis of Iodine Satellite (iSAT)

Science.gov (United States)

Mauro, Stephanie

2015-01-01

This paper presents the progress of the thermal analysis and design of the Iodine Satellite (iSAT). The purpose of the iSAT spacecraft (SC) is to demonstrate the ability of the iodine Hall Thruster propulsion system throughout a one year mission in an effort to mature the system for use on future satellites. The benefit of this propulsion system is that it uses a propellant, iodine, that is easy to store and provides a high thrust-to-mass ratio. The spacecraft will also act as a bus for an earth observation payload, the Long Wave Infrared (LWIR) Camera. Four phases of the mission, determined to either be critical to achieving requirements or phases of thermal concern, are modeled. The phases are the Right Ascension of the Ascending Node (RAAN) Change, Altitude Reduction, De-Orbit, and Science Phases. Each phase was modeled in a worst case hot environment and the coldest phase, the Science Phase, was also modeled in a worst case cold environment. The thermal environments of the spacecraft are especially important to model because iSAT has a very high power density. The satellite is the size of a 12 unit cubesat, and dissipates slightly more than 75 Watts of power as heat at times. The maximum temperatures for several components are above their maximum operational limit for one or more cases. The analysis done for the first Design and Analysis Cycle (DAC1) showed that many components were above or within 5 degrees Centigrade of their maximum operation limit. The battery is a component of concern because although it is not over its operational temperature limit, efficiency greatly decreases if it operates at the currently predicted temperatures. In the second Design and Analysis Cycle (DAC2), many steps were taken to mitigate the overheating of components, including isolating several high temperature components, removal of components, and rearrangement of systems. These changes have greatly increased the thermal margin available.

Northern Everglades, Florida, satellite image map

Science.gov (United States)

Thomas, Jean-Claude; Jones, John W.

2002-01-01

These satellite image maps are one product of the USGS Land Characteristics from Remote Sensing project, funded through the USGS Place-Based Studies Program with support from the Everglades National Park. The objective of this project is to develop and apply innovative remote sensing and geographic information system techniques to map the distribution of vegetation, vegetation characteristics, and related hydrologic variables through space and over time. The mapping and description of vegetation characteristics and their variations are necessary to accurately simulate surface hydrology and other surface processes in South Florida and to monitor land surface changes. As part of this research, data from many airborne and satellite imaging systems have been georeferenced and processed to facilitate data fusion and analysis. These image maps were created using image fusion techniques developed as part of this project.

ANALYSIS OF THE EFFECTS OF IMAGE QUALITY ON DIGITAL MAP GENERATION FROM SATELLITE IMAGES

Directory of Open Access Journals (Sweden)

H. Kim

2012-07-01

Full Text Available High resolution satellite images are widely used to produce and update a digital map since they became widely available. It is well known that the accuracy of digital map produced from satellite images is decided largely by the accuracy of geometric modelling. However digital maps are made by a series of photogrammetric workflow. Therefore the accuracy of digital maps are also affected by the quality of satellite images, such as image interpretability. For satellite images, parameters such as Modulation Transfer Function(MTF, Signal to Noise Ratio(SNR and Ground Sampling Distance(GSD are used to present images quality. Our previous research stressed that such quality parameters may not represent the quality of image products such as digital maps and that parameters for image interpretability such as Ground Resolved Distance(GRD and National Imagery Interpretability Rating Scale(NIIRS need to be considered. In this study, we analyzed the effects of the image quality on accuracy of digital maps produced by satellite images. QuickBird, IKONOS and KOMPSAT-2 imagery were used to analyze as they have similar GSDs. We measured various image quality parameters mentioned above from these images. Then we produced digital maps from the images using a digital photogrammetric workstation. We analyzed the accuracy of the digital maps in terms of their location accuracy and their level of details. Then we compared the correlation between various image quality parameters and the accuracy of digital maps. The results of this study showed that GRD and NIIRS were more critical for map production then GSD, MTF or SNR.

Design of a nano-satellite demonstrator of an infrared imaging space interferometer: the HyperCube

Science.gov (United States)

Dohlen, Kjetil; Vives, Sébastien; Rakotonimbahy, Eddy; Sarkar, Tanmoy; Tasnim Ava, Tanzila; Baccichet, Nicola; Savini, Giorgio; Swinyard, Bruce

2014-07-01

The construction of a kilometer-baseline far infrared imaging interferometer is one of the big instrumental challenges for astronomical instrumentation in the coming decades. Recent proposals such as FIRI, SPIRIT, and PFI illustrate both science cases, from exo-planetary science to study of interstellar media and cosmology, and ideas for construction of such instruments, both in space and on the ground. An interesting option for an imaging multi-aperture interferometer with km baseline is the space-based hyper telescope (HT) where a giant, sparsely populated primary mirror is constituted of several free-flying satellites each carrying a mirror segment. All the segments point the same object and direct their part of the pupil towards a common focus where another satellite, containing recombiner optics and a detector unit, is located. In Labeyrie's [1] original HT concept, perfect phasing of all the segments was assumed, allowing snap-shot imaging within a reduced field of view and coronagraphic extinction of the star. However, for a general purpose observatory, image reconstruction using closure phase a posteriori image reconstruction is possible as long as the pupil is fully non-redundant. Such reconstruction allows for much reduced alignment tolerances, since optical path length control is only required to within several tens of wavelengths, rather than within a fraction of a wavelength. In this paper we present preliminary studies for such an instrument and plans for building a miniature version to be flown on a nano satellite. A design for recombiner optics is proposed, including a scheme for exit pupil re-organization, is proposed, indicating the focal plane satellite in the case of a km-baseline interferometer could be contained within a 1m3 unit. Different options for realization of a miniature version are presented, including instruments for solar observations in the visible and the thermal infrared and giant planet observations in the visible, and an

Medical image transmission via communication satellite: evaluation of ultrasonographic images.

Science.gov (United States)

Suzuki, H; Horikoshi, H; Shiba, H; Shimamoto, S

1996-01-01

As compared with terrestrial circuits, communication satellites possess superior characteristics such as wide area coverage, broadcasting functions, high capacity, and resistance to disasters. Utilizing the narrow band channel (64 kbps) of the stationary communication satellite JCSAT1 located at an altitude of 36,000 km above the equator, we investigated satelliterelayed dynamic medical images transmitted by video signals, using hepatic ultrasonography as a model. We conclude that the "variable playing speed transmission scheme" proposed by us is effective for the transmission of dynamic images in the narrow band channel. This promises to permit diverse utilization and applications for purposes such as the transmission of other types of ultrasonic images as well as remotely directed medical diagnosis and treatment.

Velocity estimation of an airplane through a single satellite image

Institute of Scientific and Technical Information of China (English)

Zhuxin Zhao; Gongjian Wen; Bingwei Hui; Deren Li

2012-01-01

The motion information of a moving target can be recorded in a single image by a push-broom satellite. A push-broom satellite image is composed of many image lines sensed at different time instants. A method to estimate the velocity of a flying airplane from a single image based on the imagery model of the linear push-broom sensor is proposed. Some key points on the high-resolution image of the plane are chosen to determine the velocity (speed and direction). The performance of the method is tested and verified by experiments using a WorldView-1 image.%The motion information of a moving target can be recorded in a single image by a push-broom satellite.A push-broom satellite image is composed of many image lines sensed at different time instants.A method to estimate the velocity of a flying airplane from a single image based on the imagery model of the linear push-broom sensor is proposed.Some key points on the high-resolution image of the plane are chosen to determine the velocity (speed and direction).The performance of the method is tested and verified by experiments using a WorldView-1 image.

Using Fuzzy SOM Strategy for Satellite Image Retrieval and Information Mining

Directory of Open Access Journals (Sweden)

Yo-Ping Huang

2008-02-01

Full Text Available This paper proposes an efficient satellite image retrieval and knowledge discovery model. The strategy comprises two major parts. First, a computational algorithm is used for off-line satellite image feature extraction, image data representation and image retrieval. Low level features are automatically extracted from the segmented regions of satellite images. A self-organization feature map is used to construct a two-layer satellite image concept hierarchy. The events are stored in one layer and the corresponding feature vectors are categorized in the other layer. Second, a user friendly interface is provided that retrieves images of interest and mines useful information based on the events in the concept hierarchy. The proposed system is evaluated with prominent features such as typhoons or high-pressure masses.

South Florida Everglades: satellite image map

Science.gov (United States)

Jones, John W.; Thomas, Jean-Claude; Desmond, G.B.

2001-01-01

These satellite image maps are one product of the USGS Land Characteristics from Remote Sensing project, funded through the USGS Place-Based Studies Program (http://access.usgs.gov/) with support from the Everglades National Park (http://www.nps.gov/ever/). The objective of this project is to develop and apply innovative remote sensing and geographic information system techniques to map the distribution of vegetation, vegetation characteristics, and related hydrologic variables through space and over time. The mapping and description of vegetation characteristics and their variations are necessary to accurately simulate surface hydrology and other surface processes in South Florida and to monitor land surface changes. As part of this research, data from many airborne and satellite imaging systems have been georeferenced and processed to facilitate data fusion and analysis. These image maps were created using image fusion techniques developed as part of this project.

The best printing methods to print satellite images

Directory of Open Access Journals (Sweden)

G.A. Yousif

2011-12-01

In this paper different printing systems were used to print an image of SPOT-4 satellite, caver part of Sharm Elshekh area, Sinai, Egypt, on the same type of paper as much as possible, especially in the photography. This step is followed by measuring the experimental data, and analyzed colors to determine the best printing systems for satellite image printing data. The laser system is the more printing system where produce a wider range of color and highest densities of ink and access much color detail. Followed by the offset system which it recorded the best dot gain. Moreover, the study shows that it can use the advantages of each method according to the satellite image color and quantity to be produced.

Entropy-Based Block Processing for Satellite Image Registration

Directory of Open Access Journals (Sweden)

Ikhyun Lee

2012-11-01

Full Text Available Image registration is an important task in many computer vision applications such as fusion systems, 3D shape recovery and earth observation. Particularly, registering satellite images is challenging and time-consuming due to limited resources and large image size. In such scenario, state-of-the-art image registration methods such as scale-invariant feature transform (SIFT may not be suitable due to high processing time. In this paper, we propose an algorithm based on block processing via entropy to register satellite images. The performance of the proposed method is evaluated using different real images. The comparative analysis shows that it not only reduces the processing time but also enhances the accuracy.

The best printing methods to print satellite images

OpenAIRE

G.A. Yousif; R.Sh. Mohamed

2011-01-01

Printing systems operate in general as a system of color its color scale is limited as compared with the system color satellite images. Satellite image is building from very small cell named pixel, which represents the picture element and the unity of color when the image is displayed on the screen, this unit becomes lesser in size and called screen point. This unit posseses different size and shape from the method of printing to another, depending on the output resolution, tools and material...

ASTER 2002-2003 Kansas Satellite Image Database (KSID)

Data.gov (United States)

Kansas Data Access and Support Center — The Kansas Satellite Image Database (KSID):2002-2003 consists of image data gathered by three sensors. The first image data are terrain-corrected, precision...

MODIS 2002-2003 Kansas Satellite Image Database (KSID)

Data.gov (United States)

Kansas Data Access and Support Center — The Kansas Satellite Image Database (KSID):2002-2003 consists of image data gathered by three sensors. The first image data are terrain-corrected, precision...

Thermal-to-visible transducer (TVT) for thermal-IR imaging

Science.gov (United States)

Flusberg, Allen; Swartz, Stephen; Huff, Michael; Gross, Steven

2008-04-01

We have been developing a novel thermal-to-visible transducer (TVT), an uncooled thermal-IR imager that is based on a Fabry-Perot Interferometer (FPI). The FPI-based IR imager can convert a thermal-IR image to a video electronic image. IR radiation that is emitted by an object in the scene is imaged onto an IR-absorbing material that is located within an FPI. Temperature variations generated by the spatial variations in the IR image intensity cause variations in optical thickness, modulating the reflectivity seen by a probe laser beam. The reflected probe is imaged onto a visible array, producing a visible image of the IR scene. This technology can provide low-cost IR cameras with excellent sensitivity, low power consumption, and the potential for self-registered fusion of thermal-IR and visible images. We will describe characteristics of requisite pixelated arrays that we have fabricated.

Classification of high resolution satellite images

OpenAIRE

Karlsson, Anders

2003-01-01

In this thesis the Support Vector Machine (SVM)is applied on classification of high resolution satellite images. Sveral different measures for classification, including texture mesasures, 1st order statistics, and simple contextual information were evaluated. Additionnally, the image was segmented, using an enhanced watershed method, in order to improve the classification accuracy.

An Image Matching Algorithm Integrating Global SRTM and Image Segmentation for Multi-Source Satellite Imagery

Directory of Open Access Journals (Sweden)

Xiao Ling

2016-08-01

Full Text Available This paper presents a novel image matching method for multi-source satellite images, which integrates global Shuttle Radar Topography Mission (SRTM data and image segmentation to achieve robust and numerous correspondences. This method first generates the epipolar lines as a geometric constraint assisted by global SRTM data, after which the seed points are selected and matched. To produce more reliable matching results, a region segmentation-based matching propagation is proposed in this paper, whereby the region segmentations are extracted by image segmentation and are considered to be a spatial constraint. Moreover, a similarity measure integrating Distance, Angle and Normalized Cross-Correlation (DANCC, which considers geometric similarity and radiometric similarity, is introduced to find the optimal correspondences. Experiments using typical satellite images acquired from Resources Satellite-3 (ZY-3, Mapping Satellite-1, SPOT-5 and Google Earth demonstrated that the proposed method is able to produce reliable and accurate matching results.

An improved method to compute supra glacial debris thickness using thermal satellite images together with an Energy Balance Model in the Nepal Himalayas

Science.gov (United States)

Egli, Pascal; Ayala, Alvaro; Buri, Pascal; Pellicciotti, Francesca

2016-04-01

A significant proportion of Himalayan glaciers is debris covered. Knowing the thickness of the debris cover is essential to obtain accurate estimates of melt rates. Due to the remoteness of these glaciers, collecting field measurements of debris thickness for a large number of glaciers is not realistic. For this reason, previous studies have proposed an approach based on computing the energy balance at the debris surface using surface temperature from satellite imagery together with meteorological data and solving the energy balance for debris thickness. These studies differ only in the way they account for the nonlinearity of debris temperature profiles and the heat stored in the debris layer. In our study we aim to 1) assess the performance of three existing models, and 2) develop a new methodology for calculating the conductive heat flux within the debris, which accounts for the history of debris temperature profiles by solving the advection-diffusion equation of heat numerically. Additionally, we found that in the previous studies several input variables are considered as uniform and we improved this by using distributed representations. As a study case we use Lirung glacier in Langtang valley, Nepal, and we work with Landsat satellite thermal images. Results are validated using measurements of debris thickness on the glacier from October 2012 and 2015. In some cases the existing models yield realistic results. But there is very little consistency between results for different satellite images. In general, computed debris thickness is frequently too thin compared to reality. Two of the existing models were able to accurately reproduce the extent of thin debris cover on the upper part of Lirung glacier. The mean debris thickness on Lirung obtained with the existing models lies between 0.1 m and 0.3 m depending on the model used, whereby the upper value of 0.3 m corresponds best to the field measurements. Preliminary results from our new model show a larger

Smoothing of Fused Spectral Consistent Satellite Images with TV-based Edge Detection

DEFF Research Database (Denmark)

Sveinsson, Johannes; Aanæs, Henrik; Benediktsson, Jon Atli

2007-01-01

based on satellite data. Additionally, most conventional methods are loosely connected to the image forming physics of the satellite image, giving these methods an ad hoc feel. Vesteinsson et al. [1] proposed a method of fusion of satellite images that is based on the properties of imaging physics...... in a statistically meaningful way and was called spectral consistent panshapening (SCP). In this paper we improve this framework for satellite image fusion by introducing a better image prior, via data-dependent image smoothing. The dependency is obtained via total variation edge detection method.......Several widely used methods have been proposed for fusing high resolution panchromatic data and lower resolution multi-channel data. However, many of these methods fail to maintain the spectral consistency of the fused high resolution image, which is of high importance to many of the applications...

Stream temperature estimated in situ from thermal-infrared images: best estimate and uncertainty

International Nuclear Information System (INIS)

Iezzi, F; Todisco, M T

2015-01-01

The paper aims to show a technique to estimate in situ the stream temperature from thermal-infrared images deepening its best estimate and uncertainty. Stream temperature is an important indicator of water quality and nowadays its assessment is important particularly for thermal pollution monitoring in water bodies. Stream temperature changes are especially due to the anthropogenic heat input from urban wastewater and from water used as a coolant by power plants and industrial manufacturers. The stream temperatures assessment using ordinary techniques (e.g. appropriate thermometers) is limited by sparse sampling in space due to a spatial discretization necessarily punctual. Latest and most advanced techniques assess the stream temperature using thermal-infrared remote sensing based on thermal imagers placed usually on aircrafts or using satellite images. These techniques assess only the surface water temperature and they are suitable to detect the temperature of vast water bodies but do not allow a detailed and precise surface water temperature assessment in limited areas of the water body. The technique shown in this research is based on the assessment of thermal-infrared images obtained in situ via portable thermal imager. As in all thermographic techniques, also in this technique, it is possible to estimate only the surface water temperature. A stream with the presence of a discharge of urban wastewater is proposed as case study to validate the technique and to show its application limits. Since the technique analyzes limited areas in extension of the water body, it allows a detailed and precise assessment of the water temperature. In general, the punctual and average stream temperatures are respectively uncorrected and corrected. An appropriate statistical method that minimizes the errors in the average stream temperature is proposed. The correct measurement of this temperature through the assessment of thermal- infrared images obtained in situ via portable

Satellite-generated radar images of the earth

International Nuclear Information System (INIS)

Schanda, E.

1980-01-01

The Synthetic Aperture Radar (SAR) on board of SEASAT was the first non-military satellite-borne radar producing high-resolution images of the earth. Several examples of European scenes are discussed to demonstrate the properties of presently available optically processes images. (orig.)

Model-based satellite image fusion

DEFF Research Database (Denmark)

Aanæs, Henrik; Sveinsson, J. R.; Nielsen, Allan Aasbjerg

2008-01-01

A method is proposed for pixel-level satellite image fusion derived directly from a model of the imaging sensor. By design, the proposed method is spectrally consistent. It is argued that the proposed method needs regularization, as is the case for any method for this problem. A framework for pixel...... neighborhood regularization is presented. This framework enables the formulation of the regularization in a way that corresponds well with our prior assumptions of the image data. The proposed method is validated and compared with other approaches on several data sets. Lastly, the intensity......-hue-saturation method is revisited in order to gain additional insight of what implications the spectral consistency has for an image fusion method....

Interferometric Imaging of Geostationary Satellites: Signal-to-Noise Considerations

Science.gov (United States)

Jorgensen, A.; Schmitt, H.; Mozurkewich, D.; Armstrong, J.; Restaino, S.; Hindsley, R.

2011-09-01

Geostationary satellites are generally too small to image at high resolution with conventional single-dish telescopes. Obtaining many resolution elements across a typical geostationary satellite body requires a single-dish telescope with a diameter of 10’s of m or more, with a good adaptive optics system. An alternative is to use an optical/infrared interferometer consisting of multiple smaller telescopes in an array configuration. In this paper and companion papers1, 2 we discuss the performance of a common-mount 30-element interferometer. The instrument design is presented by Mozurkewich et al.,1 and imaging performance is presented by Schmitt et al.2 In this paper we discuss signal-to-noise ratio for both fringe-tracking and imaging. We conclude that the common-mount interferometer is sufficiently sensitive to track fringes on the majority of geostationary satellites. We also find that high-fidelity images can be obtained after a short integration time of a few minutes to a few tens of minutes.

Advances in analysis of pre-earthquake thermal anomalies by analyzing IR satellite data

Science.gov (United States)

Ouzounov, D.; Bryant, N.; Filizzola, C.; Pergola, N.; Taylor, P.; Tramutoli, V.

Presented work addresses the possible relationship between tectonic stress, electro-chemical and thermodynamic processes in the atmosphere and increasing infrared (IR) flux as part of a larger family of electromagnetic (EM) phenomena related to earthquake activity. Thermal infra-red (TIR) surveys performed by polar orbiting (NOAA/AVHRR, MODIS) and geosynchronous weather satellites (GOES, METEOSAT) seems to indicate the appearance (from days to weeks before the event) of "anomalous" space-time TIR transients associated with the place (epicentral area, linear structures and fault systems) and the time of occurrence of a number of major earthquakes with M>5 and focal depths no deeper than 50km. As Earth emitted in 8-14 microns range the TIR signal measured from satellite strongly vary depending on meteorological conditions and other factors (space-time changes in atmospheric transmittance, time/season, solar and satellite zenithal angles and etc) independent from seismic activity, a preliminary definition of "anomalous TIR signal" should be given. To provide reliable discrimination of thermal anomalous area from the natural events (seasonal changes, local morphology) new robust approach (RAT) has been recently proposed (and successfully applied in the field of the monitoring of the major environmental risks) that permits to give a statistically based definition of thermal info-red (TIR) anomaly and reduce of false events detection. New techniques also were specifically developed to assure the precise co-registration of all satellite scenes and permit accurate time-series analysis of satellite observations. As final results we present examples of most recent 2000/2004 worldwide strong earthquakes and the techniques used to capture the tracks of thermal emission mid-IR anomalies and methodology for practical future use of such phenomena in the early warning systems.

Phase Change Material for Temperature Control of Imager or Sounder on GOES Type Satellites in GEO

Science.gov (United States)

Choi, Michael K.

2014-01-01

This paper uses phase change material (PCM) in the scan cavity of an imager or sounder on satellites in geostationary orbit (GEO) to maintain the telescope temperature stable. When sunlight enters the scan aperture, solar heating causes the PCM to melt. When sunlight stops entering the scan aperture, the PCM releases the thermal energy stored to keep the components in the telescope warm. It has no moving parts or bimetallic springs. It reduces heater power required to make up the heat lost by radiation to space through the aperture. It is an attractive thermal control option to a radiator with a louver and a sunshade.

Image Positioning Accuracy Analysis for Super Low Altitude Remote Sensing Satellites

Directory of Open Access Journals (Sweden)

Ming Xu

2012-10-01

Full Text Available Super low altitude remote sensing satellites maintain lower flight altitudes by means of ion propulsion in order to improve image resolution and positioning accuracy. The use of engineering data in design for achieving image positioning accuracy is discussed in this paper based on the principles of the photogrammetry theory. The exact line-of-sight rebuilding of each detection element and this direction precisely intersecting with the Earth's elliptical when the camera on the satellite is imaging are both ensured by the combined design of key parameters. These parameters include: orbit determination accuracy, attitude determination accuracy, camera exposure time, accurately synchronizing the reception of ephemeris with attitude data, geometric calibration and precise orbit verification. Precise simulation calculations show that image positioning accuracy of super low altitude remote sensing satellites is not obviously improved. The attitude determination error of a satellite still restricts its positioning accuracy.

Fundamental Limitations for Imaging GEO Satellites

Science.gov (United States)

2015-10-18

Fundamental limitations for imaging GEO satellites D. Mozurkewich Seabrook Engineering , Seabrook, MD 20706 USA H. R. Schmitt, J. T. Armstrong Naval...higher spatial frequency. Send correspondence to David Mozurkewich, Seabrook Engineering , 9310 Dubarry Ave., Seabrook MD 20706 E-mail: dave

Medical image transmission via communication satellite. Evaluation of bone scintigraphy

International Nuclear Information System (INIS)

Suzuki, Hideki; Inoue, Tomio; Endo, Keigo; Shimamoto, Shigeru.

1995-01-01

As compared with terrestrial circuits, the communication satellite possesses superior characteristics such as wide area coverage, broadcasting, high capacity, and robustness to disasters. Utilizing the narrow band channel (64 kbps) of the geostationary satellite JCSAT 1 located at the altitude of 36,000 km above the equator, the authors investigated satellite-relayed medical imagings by video signals, with bone scintigraphy as a model. Each bone scintigraphy was taken by a handy-video camera, digitalized and transmitted from faculty of technology located at 25 kilometers apart from our department. Clear bone scintigraphy was obtained via satellite, as seen on the view box. Eight nuclear physicians evaluated 20 cases of bone scintigraphy. ROC (Receiver Operating Characteristic) analysis was performed between the scintigraphies on view box and via satellite by the rating method. The area under the ROC curve was 91.6±2.6% via satellite, and 93.2±2.4% on the view box and there was no significant difference between them. These results suggest that the satellite communication is very useful and effective system to send nuclear imagings to distant institutes. (author)

[Medical image transmission via communication satellite: evaluation of bone scintigraphy].

Science.gov (United States)

Suzuki, H; Inoue, T; Endo, K; Shimamoto, S

1995-10-01

As compared with terrestrial circuits, the communication satellite possesses superior characteristics such as wide area coverage, broadcasting, high capacity, and robustness to disasters. Utilizing the narrow band channel (64 kbps) of the geostationary satellite JCSAT1 located at the altitude of 36,000 km above the equator, the authors investigated satellite-relayed medical images by video signals, with bone scintigraphy as a model. Each bone scintigraphy was taken by a handy-video camera, digitalized and transmitted from faculty of technology located at 25 kilometers apart from our department. Clear bone scintigraphy was obtained via satellite, as seen on the view box. Eight nuclear physicians evaluated 20 cases of bone scintigraphy. ROC (Receiver Operating Characteristic) analysis was performed between the scintigraphies on view box and via satellite by the rating method. The area under the ROC curve was 91.6 +/- 2.6% via satellite, and 93.2 +/- 2.4% on the view box and there was no significant difference between them. These results suggest that the satellite communication is very useful and effective system to send nuclear imagings to distant institutes.

Kansas Satellite Image Database (KSID) 2004-2005

Data.gov (United States)

Kansas Data Access and Support Center — The Kansas Satellite Image Database (KSID) 2004-2005 consists of terrain-corrected, precision rectified spring, summer, and fall Landsat 5 Thematic Mapper (TM)...

Industrial application of thermal image processing and thermal control

Science.gov (United States)

Kong, Lingxue

2001-09-01

Industrial application of infrared thermography is virtually boundless as it can be used in any situations where there are temperature differences. This technology has particularly been widely used in automotive industry for process evaluation and system design. In this work, thermal image processing technique will be introduced to quantitatively calculate the heat stored in a warm/hot object and consequently, a thermal control system will be proposed to accurately and actively manage the thermal distribution within the object in accordance with the heat calculated from the thermal images.

Enhancement of Satellite Image Compression Using a Hybrid (DWT-DCT) Algorithm

Science.gov (United States)

Shihab, Halah Saadoon; Shafie, Suhaidi; Ramli, Abdul Rahman; Ahmad, Fauzan

2017-12-01

Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) image compression techniques have been utilized in most of the earth observation satellites launched during the last few decades. However, these techniques have some issues that should be addressed. The DWT method has proven to be more efficient than DCT for several reasons. Nevertheless, the DCT can be exploited to improve the high-resolution satellite image compression when combined with the DWT technique. Hence, a proposed hybrid (DWT-DCT) method was developed and implemented in the current work, simulating an image compression system on-board on a small remote sensing satellite, with the aim of achieving a higher compression ratio to decrease the onboard data storage and the downlink bandwidth, while avoiding further complex levels of DWT. This method also succeeded in maintaining the reconstructed satellite image quality through replacing the standard forward DWT thresholding and quantization processes with an alternative process that employed the zero-padding technique, which also helped to reduce the processing time of DWT compression. The DCT, DWT and the proposed hybrid methods were implemented individually, for comparison, on three LANDSAT 8 images, using the MATLAB software package. A comparison was also made between the proposed method and three other previously published hybrid methods. The evaluation of all the objective and subjective results indicated the feasibility of using the proposed hybrid (DWT-DCT) method to enhance the image compression process on-board satellites.

Schedule Optimization of Imaging Missions for Multiple Satellites and Ground Stations Using Genetic Algorithm

Science.gov (United States)

Lee, Junghyun; Kim, Heewon; Chung, Hyun; Kim, Haedong; Choi, Sujin; Jung, Okchul; Chung, Daewon; Ko, Kwanghee

2018-04-01

In this paper, we propose a method that uses a genetic algorithm for the dynamic schedule optimization of imaging missions for multiple satellites and ground systems. In particular, the visibility conflicts of communication and mission operation using satellite resources (electric power and onboard memory) are integrated in sequence. Resource consumption and restoration are considered in the optimization process. Image acquisition is an essential part of satellite missions and is performed via a series of subtasks such as command uplink, image capturing, image storing, and image downlink. An objective function for optimization is designed to maximize the usability by considering the following components: user-assigned priority, resource consumption, and image-acquisition time. For the simulation, a series of hypothetical imaging missions are allocated to a multi-satellite control system comprising five satellites and three ground stations having S- and X-band antennas. To demonstrate the performance of the proposed method, simulations are performed via three operation modes: general, commercial, and tactical.

Night vision imaging system design, integration and verification in spacecraft vacuum thermal test

Science.gov (United States)

Shang, Yonghong; Wang, Jing; Gong, Zhe; Li, Xiyuan; Pei, Yifei; Bai, Tingzhu; Zhen, Haijing

2015-08-01

The purposes of spacecraft vacuum thermal test are to characterize the thermal control systems of the spacecraft and its component in its cruise configuration and to allow for early retirement of risks associated with mission-specific and novel thermal designs. The orbit heat flux is simulating by infrared lamp, infrared cage or electric heater. As infrared cage and electric heater do not emit visible light, or infrared lamp just emits limited visible light test, ordinary camera could not operate due to low luminous density in test. Moreover, some special instruments such as satellite-borne infrared sensors are sensitive to visible light and it couldn't compensate light during test. For improving the ability of fine monitoring on spacecraft and exhibition of test progress in condition of ultra-low luminous density, night vision imaging system is designed and integrated by BISEE. System is consist of high-gain image intensifier ICCD camera, assistant luminance system, glare protect system, thermal control system and computer control system. The multi-frame accumulation target detect technology is adopted for high quality image recognition in captive test. Optical system, mechanical system and electrical system are designed and integrated highly adaptable to vacuum environment. Molybdenum/Polyimide thin film electrical heater controls the temperature of ICCD camera. The results of performance validation test shown that system could operate under vacuum thermal environment of 1.33×10-3Pa vacuum degree and 100K shroud temperature in the space environment simulator, and its working temperature is maintains at 5° during two-day test. The night vision imaging system could obtain video quality of 60lp/mm resolving power.

Thermal design and validation of radiation detector for the ChubuSat-2 micro-satellite with high-thermal-conductive graphite sheets

Science.gov (United States)

Park, Daeil; Miyata, Kikuko; Nagano, Hosei

2017-07-01

This paper describes thermal design of the radiation detector (RD) for the ChubuSat-2 with the use of high-thermal-conductive materials. ChubuSat-2 satellite is a 50-kg-class micro-satellite joint development with Nagoya University and aerospace companies. The main mission equipment of ChubuSat-2 is a RD to observe neutrons and gamma rays. However, the thermal design of the RD encounters a serious problem, such as no heater for RD and electric circuit alignment constrain. To solve this issue, the RD needs a new thermal design and thermal control for successful space missions. This paper proposes high-thermal-conductive graphite sheets to be used as a flexible radiator fin for the RD. Before the fabrication of the device, the optimal thickness and surface area for the flexible radiator fin were determined by thermal analysis. Consequently, the surface area of flexible radiator fin was determined to be 8.6×104 mm2. To verify the effects of the flexible radiator fin, we constructed a verification model and analyzed the temperature distributions in the RD. Also, the thermal vacuum test was performed using a thermal vacuum chamber, which was evacuated at a pressure of around 10-4 Pa, and its internal temperature was cooled at -80 °C by using a refrigerant. As a result, it has been demonstrated that the flexible radiator fin is effective. And the thermal vacuum test results are presented good correlation with the analysis results.

Satellite infrared imagery for thermal plume contamination monitoring in coastal ecosystem of Cernavoda NPP

Science.gov (United States)

Zoran, M. A.; Zoran, Liviu Florin V.; Dida, Adrian I.

2017-10-01

Satellite remote sensing is an important tool for spatio-temporal analysis and surveillance of NPP environment, thermal heat waste of waters being a major concern in many coastal ecosystems involving nuclear power plants. As a test case the adopted methodology was applied for 700x2 MW Cernavoda nuclear power plant (NPP) located in the South-Eastern part of Romania, which discharges warm water affecting coastal ecology. The thermal plume signatures in the NPP hydrological system have been investigated based on TIR (Thermal Infrared) spectral bands of NOAA AVHRR, Landsat TM/ETM+/OLI, and MODIS Terra/Aqua time series satellite data during 1990-2016 period. If NOAA AVHRR data proved the general pattern and extension of the thermal plume signature in Danube river and Black Sea coastal areas, Landsat TM/ETM and MODIS data used for WST (Water Surface Temperature) change detection, mapping and monitoring provided enhanced information about the plume shape, dimension and direction of dispersion in these waters. Thermal discharge from two nuclear reactors cooling is dissipated as waste heat in Danube-Black -Sea Channel and Danube River. From time-series analysis of satellite data during period 1990-2016 was found that during the winter season thermal plume was localized to an area of a few km of NPP, and the mean temperature difference between the plume and non-plume areas was about 1.7 oC. During summer and fall, derived mean temperature difference between the plume and non-plume areas was of about 1.3°C and thermal plume area was extended up to 5- 10 km far along Danube Black Sea Channel.

The SUMO Ship Detector Algorithm for Satellite Radar Images

Directory of Open Access Journals (Sweden)

Harm Greidanus

2017-03-01

Full Text Available Search for Unidentified Maritime Objects (SUMO is an algorithm for ship detection in satellite Synthetic Aperture Radar (SAR images. It has been developed over the course of more than 15 years, using a large amount of SAR images from almost all available SAR satellites operating in L-, C- and X-band. As validated by benchmark tests, it performs very well on a wide range of SAR image modes (from Spotlight to ScanSAR and resolutions (from 1–100 m and for all types and sizes of ships, within the physical limits imposed by the radar imaging. This paper describes, in detail, the algorithmic approach in all of the steps of the ship detection: land masking, clutter estimation, detection thresholding, target clustering, ship attribute estimation and false alarm suppression. SUMO is a pixel-based CFAR (Constant False Alarm Rate detector for multi-look radar images. It assumes a K distribution for the sea clutter, corrected however for deviations of the actual sea clutter from this distribution, implementing a fast and robust method for the clutter background estimation. The clustering of detected pixels into targets (ships uses several thresholds to deal with the typically irregular distribution of the radar backscatter over a ship. In a multi-polarization image, the different channels are fused. Azimuth ambiguities, a common source of false alarms in ship detection, are removed. A reliability indicator is computed for each target. In post-processing, using the results of a series of images, additional false alarms from recurrent (fixed targets including range ambiguities are also removed. SUMO can run in semi-automatic mode, where an operator can verify each detected target. It can also run in fully automatic mode, where batches of over 10,000 images have successfully been processed in less than two hours. The number of satellite SAR systems keeps increasing, as does their application to maritime surveillance. The open data policy of the EU�

AN APPROACH FOR STITCHING SATELLITE IMAGES IN A BIGDATA MAPREDUCE FRAMEWORK

Directory of Open Access Journals (Sweden)

H. Sarı

2017-11-01

Full Text Available In this study we present a two-step map/reduce framework to stitch satellite mosaic images. The proposed system enable recognition and extraction of objects whose parts falling in separate satellite mosaic images. However this is a time and resource consuming process. The major aim of the study is improving the performance of the image stitching processes by utilizing big data framework. To realize this, we first convert the images into bitmaps (first mapper and then String formats in the forms of 255s and 0s (second mapper, and finally, find the best possible matching position of the images by a reduce function.

An Approach for Stitching Satellite Images in a Bigdata Mapreduce Framework

Science.gov (United States)

Sarı, H.; Eken, S.; Sayar, A.

2017-11-01

In this study we present a two-step map/reduce framework to stitch satellite mosaic images. The proposed system enable recognition and extraction of objects whose parts falling in separate satellite mosaic images. However this is a time and resource consuming process. The major aim of the study is improving the performance of the image stitching processes by utilizing big data framework. To realize this, we first convert the images into bitmaps (first mapper) and then String formats in the forms of 255s and 0s (second mapper), and finally, find the best possible matching position of the images by a reduce function.

Detecting aircrafts from satellite images using saliency and conical ...

Indian Academy of Sciences (India)

Samik Banerjee

automatically detect all kinds of interesting targets in satellite images. .... which is used for text and image categorization, has been also introduced for object ...... 3.4 GHz processor, 32 GB RAM and Windows 7 (64 bit). Operating System. 6.

Design of an Image Motion Compenstaion (IMC Algorithm for Image Registration of the Communication, Ocean, Meteorolotical Satellite (COMS-1

Directory of Open Access Journals (Sweden)

Taek Seo Jung

2006-03-01

Full Text Available This paper presents an Image Motion Compensation (IMC algorithm for the Korea's Communication, Ocean, and Meteorological Satellite (COMS-1. An IMC algorithm is a priority component of image registration in Image Navigation and Registration (INR system to locate and register radiometric image data. Due to various perturbations, a satellite has orbit and attitude errors with respect to a reference motion. These errors cause depointing of the imager aiming direction, and in consequence cause image distortions. To correct the depointing of the imager aiming direction, a compensation algorithm is designed by adapting different equations from those used for the GOES satellites. The capability of the algorithm is compared with that of existing algorithm applied to the GOES's INR system. The algorithm developed in this paper improves pointing accuracy by 40%, and efficiently compensates the depointings of the imager aiming direction.

The Application of the Technology of 3D Satellite Cloud Imaging in Virtual Reality Simulation

Directory of Open Access Journals (Sweden)

Xiao-fang Xie

2007-05-01

Full Text Available Using satellite cloud images to simulate clouds is one of the new visual simulation technologies in Virtual Reality (VR. Taking the original data of satellite cloud images as the source, this paper depicts specifically the technology of 3D satellite cloud imaging through the transforming of coordinates and projection, creating a DEM (Digital Elevation Model of cloud imaging and 3D simulation. A Mercator projection was introduced to create a cloud image DEM, while solutions for geodetic problems were introduced to calculate distances, and the outer-trajectory science of rockets was introduced to obtain the elevation of clouds. For demonstration, we report on a computer program to simulate the 3D satellite cloud images.

Geometric calibration of ERS satellite SAR images

DEFF Research Database (Denmark)

Mohr, Johan Jacob; Madsen, Søren Nørvang

2001-01-01

Geometric calibration of the European Remote Sensing (ERS) Satellite synthetic aperture radar (SAR) slant range images is important in relation to mapping areas without ground reference points and also in relation to automated processing. The relevant SAR system parameters are discussed...

A data mining approach for sharpening satellite thermal imagery over land

Science.gov (United States)

Thermal infrared (TIR) imagery is normally acquired at coarser pixel resolution than that of shortwave sensors on the same satellite platform and often the TIR resolution is not suitable for monitoring crop conditions of individual fields or the impacts of land cover changes which are at significant...

Ice Sheet Change Detection by Satellite Image Differencing

Science.gov (United States)

Bindschadler, Robert A.; Scambos, Ted A.; Choi, Hyeungu; Haran, Terry M.

2010-01-01

Differencing of digital satellite image pairs highlights subtle changes in near-identical scenes of Earth surfaces. Using the mathematical relationships relevant to photoclinometry, we examine the effectiveness of this method for the study of localized ice sheet surface topography changes using numerical experiments. We then test these results by differencing images of several regions in West Antarctica, including some where changes have previously been identified in altimeter profiles. The technique works well with coregistered images having low noise, high radiometric sensitivity, and near-identical solar illumination geometry. Clouds and frosts detract from resolving surface features. The ETM(plus) sensor on Landsat-7, ALI sensor on EO-1, and MODIS sensor on the Aqua and Terra satellite platforms all have potential for detecting localized topographic changes such as shifting dunes, surface inflation and deflation features associated with sub-glacial lake fill-drain events, or grounding line changes. Availability and frequency of MODIS images favor this sensor for wide application, and using it, we demonstrate both qualitative identification of changes in topography and quantitative mapping of slope and elevation changes.

Thermal diffusivity imaging with the thermal lens microscope.

Science.gov (United States)

Dada, Oluwatosin O; Feist, Peter E; Dovichi, Norman J

2011-12-01

A coaxial thermal lens microscope was used to generate images based on both the absorbance and thermal diffusivity of histological samples. A pump beam was modulated at frequencies ranging from 50 kHz to 5 MHz using an acousto-optic modulator. The pump and a CW probe beam were combined with a dichroic mirror, directed into an inverted microscope, and focused onto the specimen. The change in the transmitted probe beam's center intensity was detected with a photodiode. The photodiode's signal and a reference signal from the modulator were sent to a high-speed lock-in amplifier. The in-phase and quadrature signals were recorded as a sample was translated through the focused beams and used to generate images based on the amplitude and phase of the lock-in amplifier's signal. The amplitude is related to the absorbance and the phase is related to the thermal diffusivity of the sample. Thin sections of stained liver and bone tissues were imaged; the contrast and signal-to-noise ratio of the phase image was highest at frequencies from 0.1-1 MHz and dropped at higher frequencies. The spatial resolution was 2.5 μm for both amplitude and phase images, limited by the pump beam spot size. © 2011 Optical Society of America

Thermal imaging cameras characteristics and performance

CERN Document Server

Williams, Thomas

2009-01-01

The ability to see through smoke and mist and the ability to use the variances in temperature to differentiate between targets and their backgrounds are invaluable in military applications and have become major motivators for the further development of thermal imagers. As the potential of thermal imaging is more clearly understood and the cost decreases, the number of industrial and civil applications being exploited is growing quickly. In order to evaluate the suitability of particular thermal imaging cameras for particular applications, it is important to have the means to specify and measur

Landsat TM and ETM+ 2002-2003 Kansas Satellite Image Database (KSID)

Data.gov (United States)

Kansas Data Access and Support Center — The Kansas Satellite Image Database (KSID):2002-2003 consists of image data gathered by three sensors. The first image data are terrain-corrected, precision...

RELATIVE ORIENTATION AND MODIFIED PIECEWISE EPIPOLAR RESAMPLING FOR HIGH RESOLUTION SATELLITE IMAGES

Directory of Open Access Journals (Sweden)

K. Gong

2017-05-01

Full Text Available High resolution, optical satellite sensors are boosted to a new era in the last few years, because satellite stereo images at half meter or even 30cm resolution are available. Nowadays, high resolution satellite image data have been commonly used for Digital Surface Model (DSM generation and 3D reconstruction. It is common that the Rational Polynomial Coefficients (RPCs provided by the vendors have rough precision and there is no ground control information available to refine the RPCs. Therefore, we present two relative orientation methods by using corresponding image points only: the first method will use quasi ground control information, which is generated from the corresponding points and rough RPCs, for the bias-compensation model; the second method will estimate the relative pointing errors on the matching image and remove this error by an affine model. Both methods do not need ground control information and are applied for the entire image. To get very dense point clouds, the Semi-Global Matching (SGM method is an efficient tool. However, before accomplishing the matching process the epipolar constraints are required. In most conditions, satellite images have very large dimensions, contrary to the epipolar geometry generation and image resampling, which is usually carried out in small tiles. This paper also presents a modified piecewise epipolar resampling method for the entire image without tiling. The quality of the proposed relative orientation and epipolar resampling method are evaluated, and finally sub-pixel accuracy has been achieved in our work.

Image Fusion-Based Land Cover Change Detection Using Multi-Temporal High-Resolution Satellite Images

Directory of Open Access Journals (Sweden)

Biao Wang

2017-08-01

Full Text Available Change detection is usually treated as a problem of explicitly detecting land cover transitions in satellite images obtained at different times, and helps with emergency response and government management. This study presents an unsupervised change detection method based on the image fusion of multi-temporal images. The main objective of this study is to improve the accuracy of unsupervised change detection from high-resolution multi-temporal images. Our method effectively reduces change detection errors, since spatial displacement and spectral differences between multi-temporal images are evaluated. To this end, a total of four cross-fused images are generated with multi-temporal images, and the iteratively reweighted multivariate alteration detection (IR-MAD method—a measure for the spectral distortion of change information—is applied to the fused images. In this experiment, the land cover change maps were extracted using multi-temporal IKONOS-2, WorldView-3, and GF-1 satellite images. The effectiveness of the proposed method compared with other unsupervised change detection methods is demonstrated through experimentation. The proposed method achieved an overall accuracy of 80.51% and 97.87% for cases 1 and 2, respectively. Moreover, the proposed method performed better when differentiating the water area from the vegetation area compared to the existing change detection methods. Although the water area beneath moderate and sparse vegetation canopy was captured, vegetation cover and paved regions of the water body were the main sources of omission error, and commission errors occurred primarily in pixels of mixed land use and along the water body edge. Nevertheless, the proposed method, in conjunction with high-resolution satellite imagery, offers a robust and flexible approach to land cover change mapping that requires no ancillary data for rapid implementation.

Thermal IR satellite data application for earthquake research in Pakistan

Science.gov (United States)

Barkat, Adnan; Ali, Aamir; Rehman, Khaista; Awais, Muhammad; Riaz, Muhammad Shahid; Iqbal, Talat

2018-05-01

The scientific progress in space research indicates earthquake-related processes of surface temperature growth, gas/aerosol exhalation and electromagnetic disturbances in the ionosphere prior to seismic activity. Among them surface temperature growth calculated using the satellite thermal infrared images carries valuable earthquake precursory information for near/distant earthquakes. Previous studies have concluded that such information can appear few days before the occurrence of an earthquake. The objective of this study is to use MODIS thermal imagery data for precursory analysis of Kashmir (Oct 8, 2005; Mw 7.6; 26 km), Ziarat (Oct 28, 2008; Mw 6.4; 13 km) and Dalbandin (Jan 18, 2011; Mw 7.2; 69 km) earthquakes. Our results suggest that there exists an evident correlation of Land Surface Temperature (thermal; LST) anomalies with seismic activity. In particular, a rise of 3-10 °C in LST is observed 6, 4 and 14 days prior to Kashmir, Ziarat and Dalbandin earthquakes. In order to further elaborate our findings, we have presented a comparative and percentile analysis of daily and five years averaged LST for a selected time window with respect to the month of earthquake occurrence. Our comparative analyses of daily and five years averaged LST show a significant change of 6.5-7.9 °C for Kashmir, 8.0-8.1 °C for Ziarat and 2.7-5.4 °C for Dalbandin earthquakes. This significant change has high percentile values for the selected events i.e. 70-100% for Kashmir, 87-100% for Ziarat and 84-100% for Dalbandin earthquakes. We expect that such consistent results may help in devising an optimal earthquake forecasting strategy and to mitigate the effect of associated seismic hazards.

Accuracy assessment of topographic mapping using UAV image integrated with satellite images

International Nuclear Information System (INIS)

Azmi, S M; Ahmad, Baharin; Ahmad, Anuar

2014-01-01

Unmanned Aerial Vehicle or UAV is extensively applied in various fields such as military applications, archaeology, agriculture and scientific research. This study focuses on topographic mapping and map updating. UAV is one of the alternative ways to ease the process of acquiring data with lower operating costs, low manufacturing and operational costs, plus it is easy to operate. Furthermore, UAV images will be integrated with QuickBird images that are used as base maps. The objective of this study is to make accuracy assessment and comparison between topographic mapping using UAV images integrated with aerial photograph and satellite image. The main purpose of using UAV image is as a replacement for cloud covered area which normally exists in aerial photograph and satellite image, and for updating topographic map. Meanwhile, spatial resolution, pixel size, scale, geometric accuracy and correction, image quality and information contents are important requirements needed for the generation of topographic map using these kinds of data. In this study, ground control points (GCPs) and check points (CPs) were established using real time kinematic Global Positioning System (RTK-GPS) technique. There are two types of analysis that are carried out in this study which are quantitative and qualitative assessments. Quantitative assessment is carried out by calculating root mean square error (RMSE). The outputs of this study include topographic map and orthophoto. From this study, the accuracy of UAV image is ± 0.460 m. As conclusion, UAV image has the potential to be used for updating of topographic maps

Recurrent Neural Networks to Correct Satellite Image Classification Maps

Science.gov (United States)

Maggiori, Emmanuel; Charpiat, Guillaume; Tarabalka, Yuliya; Alliez, Pierre

2017-09-01

While initially devised for image categorization, convolutional neural networks (CNNs) are being increasingly used for the pixelwise semantic labeling of images. However, the proper nature of the most common CNN architectures makes them good at recognizing but poor at localizing objects precisely. This problem is magnified in the context of aerial and satellite image labeling, where a spatially fine object outlining is of paramount importance. Different iterative enhancement algorithms have been presented in the literature to progressively improve the coarse CNN outputs, seeking to sharpen object boundaries around real image edges. However, one must carefully design, choose and tune such algorithms. Instead, our goal is to directly learn the iterative process itself. For this, we formulate a generic iterative enhancement process inspired from partial differential equations, and observe that it can be expressed as a recurrent neural network (RNN). Consequently, we train such a network from manually labeled data for our enhancement task. In a series of experiments we show that our RNN effectively learns an iterative process that significantly improves the quality of satellite image classification maps.

Response of turkey muscle satellite cells to thermal challenge. I. transcriptome effects in proliferating cells.

Science.gov (United States)

Reed, Kent M; Mendoza, Kristelle M; Abrahante, Juan E; Barnes, Natalie E; Velleman, Sandra G; Strasburg, Gale M

2017-05-06

Climate change poses a multi-dimensional threat to food and agricultural systems as a result of increased risk to animal growth, development, health, and food product quality. This study was designed to characterize transcriptional changes induced in turkey muscle satellite cells cultured under cold or hot thermal challenge to better define molecular mechanisms by which thermal stress alters breast muscle ultrastructure. Satellite cells isolated from the pectoralis major muscle of 7-weeks-old male turkeys from two breeding lines (16 weeks body weight-selected and it's randombred control) were proliferated in culture at 33 °C, 38 °C or 43 °C for 72 h. Total RNA was isolated and 12 libraries subjected to RNAseq analysis. Statistically significant differences in gene expression were observed among treatments and between turkey lines with a greater number of genes altered by cold treatment than by hot and fewer differences observed between lines than between temperatures. Pathway analysis found that cold treatment resulted in an overrepresentation of genes involved in cell signaling/signal transduction and cell communication/cell signaling as compared to control (38 °C). Heat-treated muscle satellite cells showed greater tendency towards expression of genes related to muscle system development and differentiation. This study demonstrates significant transcriptome effects on turkey skeletal muscle satellite cells exposed to thermal challenge. Additional effects on gene expression could be attributed to genetic selection for 16 weeks body weight (muscle mass). New targets are identified for further research on the differential control of satellite cell proliferation in poultry.

Images of war: using satellite images for human rights monitoring in Turkish Kurdistan.

Science.gov (United States)

de Vos, Hugo; Jongerden, Joost; van Etten, Jacob

2008-09-01

In areas of war and armed conflict it is difficult to get trustworthy and coherent information. Civil society and human rights groups often face problems of dealing with fragmented witness reports, disinformation of war propaganda, and difficult direct access to these areas. Turkish Kurdistan was used as a case study of armed conflict to evaluate the potential use of satellite images for verification of witness reports collected by human rights groups. The Turkish army was reported to be burning forests, fields and villages as a strategy in the conflict against guerrilla uprising. This paper concludes that satellite images are useful to validate witness reports of forest fires. Even though the use of this technology for human rights groups will depend on some feasibility factors such as prices, access and expertise, the images proved to be key for analysis of spatial aspects of conflict and valuable for reconstructing a more trustworthy picture.

Improving Eastern Bluebird nest box performance using computer analysis of satellite images

Directory of Open Access Journals (Sweden)

Sarah Svatora

2012-06-01

Full Text Available Bird conservationists have been introducing man-made boxes in an effort to increase the bluebird population. In this study we use computer analysis of satellite images to show that the performance of the boxes used by Eastern Bluebirds (Sialia sialis in Michigan can be improved by about 48%. The analysis is based on a strongcorrelation found between the edge directionality measured in the satellite image of the area around the box, and the preferences of the birds when selecting their nesting site. The method is based on satellite images taken from Google Earth, and can be used by conservationists to select a box placement strategy that will optimize the efficacy of the boxes deployed in a given area.

Auto Mission Planning System Design for Imaging Satellites and Its Applications in Environmental Field

Directory of Open Access Journals (Sweden)

He Yongming

2016-10-01

Full Text Available Satellite hardware has reached a level of development that enables imaging satellites to realize applications in the area of meteorology and environmental monitoring. As the requirements in terms of feasibility and the actual profit achieved by satellite applications increase, we need to comprehensively consider the actual status, constraints, unpredictable information, and complicated requirements. The management of this complex information and the allocation of satellite resources to realize image acquisition have become essential for enhancing the efficiency of satellite instrumentation. In view of this, we designed a satellite auto mission planning system, which includes two sub-systems: the imaging satellite itself and the ground base, and these systems would then collaborate to process complicated missions: the satellite mainly focuses on mission planning and functions according to actual parameters, whereas the ground base provides auxiliary information, management, and control. Based on the requirements analysis, we have devised the application scenarios, main module, and key techniques. Comparison of the simulation results of the system, confirmed the feasibility and optimization efficiency of the system framework, which also stimulates new thinking for the method of monitoring environment and design of mission planning systems.

Ghost imaging with third-order correlated thermal light

International Nuclear Information System (INIS)

Ou, L-H; Kuang, L-M

2007-01-01

In this paper, we propose a ghost imaging scheme with third-order correlated thermal light. We show that it is possible to produce the spatial information of an object at two different places in a nonlocal fashion by means of a third-order correlated imaging process with a third-order correlated thermal source and third-order correlation measurement. Concretely, we propose a protocol to create two ghost images at two different places from one object. This protocol involves two optical configurations. We derive the Gaussian thin lens equations and plot the geometrical optics of the ghost imaging processes for the two configurations. It is indicated that third-order correlated ghost imaging with thermal light exhibits richer correlated imaging effects than second-order correlated ghost imaging with thermal light

Convolutional neural network features based change detection in satellite images

Science.gov (United States)

Mohammed El Amin, Arabi; Liu, Qingjie; Wang, Yunhong

2016-07-01

With the popular use of high resolution remote sensing (HRRS) satellite images, a huge research efforts have been placed on change detection (CD) problem. An effective feature selection method can significantly boost the final result. While hand-designed features have proven difficulties to design features that effectively capture high and mid-level representations, the recent developments in machine learning (Deep Learning) omit this problem by learning hierarchical representation in an unsupervised manner directly from data without human intervention. In this letter, we propose approaching the change detection problem from a feature learning perspective. A novel deep Convolutional Neural Networks (CNN) features based HR satellite images change detection method is proposed. The main guideline is to produce a change detection map directly from two images using a pretrained CNN. This method can omit the limited performance of hand-crafted features. Firstly, CNN features are extracted through different convolutional layers. Then, a concatenation step is evaluated after an normalization step, resulting in a unique higher dimensional feature map. Finally, a change map was computed using pixel-wise Euclidean distance. Our method has been validated on real bitemporal HRRS satellite images according to qualitative and quantitative analyses. The results obtained confirm the interest of the proposed method.

Experimental design for the evaluation of high-T(sub c) superconductive thermal bridges in a sensor satellite

Science.gov (United States)

Scott, Elaine P.; Lee, Kasey M.

1994-01-01

Infrared sensor satellites, which consist of cryogenic infrared sensor detectors, electrical instrumentation, and data acquisition systems, are used to monitor the conditions of the earth's upper atmosphere in order to evaluate its present and future changes. Currently, the electrical connections (instrumentation), which act as thermal bridges between the cryogenic infrared sensor and the significantly warmer data acquisition unit of the sensor satellite system, constitute a significant portion of the heat load on the cryogen. As a part of extending the mission life of the sensor satellite system, the researchers at the National Aeronautics and Space Administration's Langley Research Center (NASA-LaRC) are evaluating the effectiveness of replacing the currently used manganin wires with high-temperature superconductive (HTS) materials as the electrical connections (thermal bridges). In conjunction with the study being conducted at NASA-LaRC, the proposed research is to design a space experiment to determine the thermal savings on a cryogenic subsystem when manganin leads are replaced by HTS leads printed onto a substrate with a low thermal conductivity, and to determine the thermal conductivities of HTS materials. The experiment is designed to compare manganin wires with two different types of superconductors on substrates by determining the heat loss by the thermal bridges and providing temperature measurements for the estimation of thermal conductivity. A conductive mathematical model has been developed and used as a key tool in the design process and subsequent analysis.

Thermal infrared panoramic imaging sensor

Science.gov (United States)

Gutin, Mikhail; Tsui, Eddy K.; Gutin, Olga; Wang, Xu-Ming; Gutin, Alexey

2006-05-01

Panoramic cameras offer true real-time, 360-degree coverage of the surrounding area, valuable for a variety of defense and security applications, including force protection, asset protection, asset control, security including port security, perimeter security, video surveillance, border control, airport security, coastguard operations, search and rescue, intrusion detection, and many others. Automatic detection, location, and tracking of targets outside protected area ensures maximum protection and at the same time reduces the workload on personnel, increases reliability and confidence of target detection, and enables both man-in-the-loop and fully automated system operation. Thermal imaging provides the benefits of all-weather, 24-hour day/night operation with no downtime. In addition, thermal signatures of different target types facilitate better classification, beyond the limits set by camera's spatial resolution. The useful range of catadioptric panoramic cameras is affected by their limited resolution. In many existing systems the resolution is optics-limited. Reflectors customarily used in catadioptric imagers introduce aberrations that may become significant at large camera apertures, such as required in low-light and thermal imaging. Advantages of panoramic imagers with high image resolution include increased area coverage with fewer cameras, instantaneous full horizon detection, location and tracking of multiple targets simultaneously, extended range, and others. The Automatic Panoramic Thermal Integrated Sensor (APTIS), being jointly developed by Applied Science Innovative, Inc. (ASI) and the Armament Research, Development and Engineering Center (ARDEC) combines the strengths of improved, high-resolution panoramic optics with thermal imaging in the 8 - 14 micron spectral range, leveraged by intelligent video processing for automated detection, location, and tracking of moving targets. The work in progress supports the Future Combat Systems (FCS) and the

FFT-enhanced IHS transform method for fusing high-resolution satellite images

Science.gov (United States)

Ling, Y.; Ehlers, M.; Usery, E.L.; Madden, M.

2007-01-01

Existing image fusion techniques such as the intensity-hue-saturation (IHS) transform and principal components analysis (PCA) methods may not be optimal for fusing the new generation commercial high-resolution satellite images such as Ikonos and QuickBird. One problem is color distortion in the fused image, which causes visual changes as well as spectral differences between the original and fused images. In this paper, a fast Fourier transform (FFT)-enhanced IHS method is developed for fusing new generation high-resolution satellite images. This method combines a standard IHS transform with FFT filtering of both the panchromatic image and the intensity component of the original multispectral image. Ikonos and QuickBird data are used to assess the FFT-enhanced IHS transform method. Experimental results indicate that the FFT-enhanced IHS transform method may improve upon the standard IHS transform and the PCA methods in preserving spectral and spatial information. ?? 2006 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS).

Performance Evaluation of Three Different High Resolution Satellite Images in Semi-Automatic Urban Illegal Building Detection

Science.gov (United States)

Khalilimoghadama, N.; Delavar, M. R.; Hanachi, P.

2017-09-01

The problem of overcrowding of mega cities has been bolded in recent years. To meet the need of housing this increased population, which is of great importance in mega cities, a huge number of buildings are constructed annually. With the ever-increasing trend of building constructions, we are faced with the growing trend of building infractions and illegal buildings (IBs). Acquiring multi-temporal satellite images and using change detection techniques is one of the proper methods of IB monitoring. Using the type of satellite images with different spatial and spectral resolutions has always been an issue in efficient detection of the building changes. In this research, three bi-temporal high-resolution satellite images of IRS-P5, GeoEye-1 and QuickBird sensors acquired from the west of metropolitan area of Tehran, capital of Iran, in addition to city maps and municipality property database were used to detect the under construction buildings with improved performance and accuracy. Furthermore, determining the employed bi-temporal satellite images to provide better performance and accuracy in the case of IB detection is the other purpose of this research. The Kappa coefficients of 70 %, 64 %, and 68 % were obtained for producing change image maps using GeoEye-1, IRS-P5, and QuickBird satellite images, respectively. In addition, the overall accuracies of 100 %, 6 %, and 83 % were achieved for IB detection using the satellite images, respectively. These accuracies substantiate the fact that the GeoEye-1 satellite images had the best performance among the employed images in producing change image map and detecting the IBs.

Spatial Data Exploring by Satellite Image Distributed Processing

Science.gov (United States)

Mihon, V. D.; Colceriu, V.; Bektas, F.; Allenbach, K.; Gvilava, M.; Gorgan, D.

2012-04-01

Our society needs and environmental predictions encourage the applications development, oriented on supervising and analyzing different Earth Science related phenomena. Satellite images could be explored for discovering information concerning land cover, hydrology, air quality, and water and soil pollution. Spatial and environment related data could be acquired by imagery classification consisting of data mining throughout the multispectral bands. The process takes in account a large set of variables such as satellite image types (e.g. MODIS, Landsat), particular geographic area, soil composition, vegetation cover, and generally the context (e.g. clouds, snow, and season). All these specific and variable conditions require flexible tools and applications to support an optimal search for the appropriate solutions, and high power computation resources. The research concerns with experiments on solutions of using the flexible and visual descriptions of the satellite image processing over distributed infrastructures (e.g. Grid, Cloud, and GPU clusters). This presentation highlights the Grid based implementation of the GreenLand application. The GreenLand application development is based on simple, but powerful, notions of mathematical operators and workflows that are used in distributed and parallel executions over the Grid infrastructure. Currently it is used in three major case studies concerning with Istanbul geographical area, Rioni River in Georgia, and Black Sea catchment region. The GreenLand application offers a friendly user interface for viewing and editing workflows and operators. The description involves the basic operators provided by GRASS [1] library as well as many other image related operators supported by the ESIP platform [2]. The processing workflows are represented as directed graphs giving the user a fast and easy way to describe complex parallel algorithms, without having any prior knowledge of any programming language or application commands

Small-satellite technology and applications; Proceedings of the Meeting, Orlando, FL, Apr. 4, 5, 1991

Science.gov (United States)

Horais, Brian J.

Remote sensing applications and systems, small satellites for sensing missions, and supporting technologies are the broad topics discussed. Particular papers are presented on small satellites for water cycle experiments, low-cost spacecraft buses for remote sensing applications, Webersat (a low-cost imaging satellite), DARPA initiatives in small-satellite technologies, a solid-state magnetic azimuth sensor for small satellites, and thermal analysis of a small expendable tether satellite package. (For individual items see A93-24152 to A93-24175)

Mathematical modeling of a new satellite thermal architecture system connecting the east and west radiator panels and flight performance prediction

International Nuclear Information System (INIS)

Torres, Alejandro; Mishkinis, Donatas; Kaya, Tarik

2014-01-01

An entirely novel satellite thermal architecture, connecting the east and west radiators of a geostationary telecommunications satellite via loop heat pipes (LHPs), is proposed. The LHP operating temperature is regulated by using pressure regulating valves (PRVs). A transient numerical model is developed to simulate the thermal dynamic behavior of the proposed system. The details of the proposed architecture and mathematical model are presented. The model is used to analyze a set of critical design cases to identify potential failure modes prior to the qualification and in-orbit tests. The mathematical model results for critical cases are presented and discussed. The model results demonstrated the robustness and versatility of the proposed architecture under the predicted worst-case conditions. - Highlights: •We developed a mathematical model of a novel satellite thermal architecture. •We provided the dimensioning cases to design the thermal architecture. •We provided the failure mode cases to verify the thermal architecture. •We provided the results of the corresponding dimensioning and failure cases

Very high resolution satellite data: New challenges in image analysis

Digital Repository Service at National Institute of Oceanography (India)

Sathe, P.V.; Muraleedharan, P.M.

with the exception that a ground-based view covers the entire optical range from 400 to 700 nm while satellite images will be wavelength-specific. Although the images will not surpass details observed by a human eye, they will, in principle, be comparable with aerial...

Landsat TM and ETM+ Kansas Satellite Image Database (KSID)

Data.gov (United States)

Kansas Data Access and Support Center — The Kansas Satellite Image Database (KSID):2000-2001 consists of terrain-corrected, precision rectified spring, summer, and fall Landsat 5 Thematic Mapper (TM) and...

a Semi-Empirical Topographic Correction Model for Multi-Source Satellite Images

Science.gov (United States)

Xiao, Sa; Tian, Xinpeng; Liu, Qiang; Wen, Jianguang; Ma, Yushuang; Song, Zhenwei

2018-04-01

Topographic correction of surface reflectance in rugged terrain areas is the prerequisite for the quantitative application of remote sensing in mountainous areas. Physics-based radiative transfer model can be applied to correct the topographic effect and accurately retrieve the reflectance of the slope surface from high quality satellite image such as Landsat8 OLI. However, as more and more images data available from various of sensors, some times we can not get the accurate sensor calibration parameters and atmosphere conditions which are needed in the physics-based topographic correction model. This paper proposed a semi-empirical atmosphere and topographic corrction model for muti-source satellite images without accurate calibration parameters.Based on this model we can get the topographic corrected surface reflectance from DN data, and we tested and verified this model with image data from Chinese satellite HJ and GF. The result shows that the correlation factor was reduced almost 85 % for near infrared bands and the classification overall accuracy of classification increased 14 % after correction for HJ. The reflectance difference of slope face the sun and face away the sun have reduced after correction.

Next generation thermal imaging

International Nuclear Information System (INIS)

Marche, P.P.

1988-01-01

The best design of high performance thermal imagers for the 1990s will use horizontal quasi-linear arrays with focal plane processing associated with a simple vertical mechanical scanner. These imagers will have performance that is greatly improved compared to that of present-day devices (50 to 100 percent range and resolution improvement). 5 references

Detection of jet contrails from satellite images

Science.gov (United States)

Meinert, Dieter

1994-02-01

In order to investigate the influence of modern technology on the world climate it is important to have automatic detection methods for man-induced parameters. In this case the influence of jet contrails on the greenhouse effect shall be investigated by means of images from polar orbiting satellites. Current methods of line recognition and amplification cannot distinguish between contrails and rather sharp edges of natural cirrus or noise. They still rely on human control. Through the combination of different methods from cloud physics, image comparison, pattern recognition, and artificial intelligence we try to overcome this handicap. Here we will present the basic methods applied to each image frame, and list preliminary results derived this way.

GRANULOMETRIC MAPS FROM HIGH RESOLUTION SATELLITE IMAGES

Directory of Open Access Journals (Sweden)

Catherine Mering

2011-05-01

Full Text Available A new method of land cover mapping from satellite images using granulometric analysis is presented here. Discontinuous landscapes such as steppian bushes of semi arid regions and recently growing urban settlements are especially concerned by this study. Spatial organisations of the land cover are quantified by means of the size distribution analysis of the land cover units extracted from high resolution remotely sensed images. A granulometric map is built by automatic classification of every pixel of the image according to the granulometric density inside a sliding neighbourhood. Granulometric mapping brings some advantages over traditional thematic mapping by remote sensing by focusing on fine spatial events and small changes in one peculiar category of the landscape.

METEOROLOGICAL SATELLITE IMAGES IN GEOGRAPHY CLASSES: a didactic possibility

Directory of Open Access Journals (Sweden)

Diego Correia Maia

2016-01-01

Full Text Available ABSTRACT: The satellite images are still largely unexplored as didactic resource in geography classes, particularly about meteorology. This article aims to contribute to the development of new methodologies of interpretation and understanding, beyond the construction of pedagogical practices involving meteorological satellite images, concepts and issues related to climate issues. The aim of this paper is to present possibilities for the use of meteorological satellite images in the Teaching of Geography, aiming the promoting and the understanding of contents of air masses and fronts and climatic factors. RESUMO: As imagens de satélite ainda são pouco exploradas como recurso didático nas aulas de Geografia, principalmente aquelas relativas à meteorologia. Este artigo visa contribuir com o desenvolvimento de novas metodologias de interpretação e compreensão, além da construção de práticas pedagógicas envolvendo imagens de satélite meteorológico, conceitos e temas ligados às questões climáticas. Seu objetivo é apresentar possibilidades de utilização das imagens de satélite meteorológico no Ensino de Geografia, visando à promoção e ao entendimento dos conteúdos de massas de ar e frentes e de elementos climáticos. Palavras chave

Evaluating thermal image sharpening over irrigated crops in a desert environment

KAUST Repository

Rosas, Jorge

2014-09-01

Satellite remote sensing provides spatially and temporally distributed data on land surface characteristics, useful for mapping land surface energy fluxes and evapotranspiration (ET). Multi-spectral platforms, including Landsat and the Moderate Resolution Imaging Spectroradiometer (MODIS), acquire imagery in the visible to shortwave infrared and thermal infrared (TIR) domain at resolutions ranging from 30 to 1000 m. Land-surface temperature (LST) derived from TIR satellite data has been reliably used as a remote indicator of ET and surface moisture status. However, TIR imagery usually operates at a coarser resolution than that of shortwave sensors on the same satellite platform, making it sometimes unsuitable for monitoring of field-scale crop conditions. As a result, several techniques for thermal sharpening have been developed. In this study, the data mining sharpener (DMS; Gao et al., 2012) technique is applied over irrigated farming areas located in harsh desert environments in Saudi Arabia. The DMS approach sharpens TIR imagery using finer resolution shortwave spectral reflectances and functional LST and reflectance relationships established using a flexible regression tree approach. In this study, the DMS is applied to Landsat 8 data (100m TIR resolution), which is scaled up to 240m, 480m, and 960m in order to assess the accuracy of the DMS technique in arid irrigated farming environments for different sharpening ratios. Furthermore, the scaling done on Landsat 8 data is consistent with the resolution of MODIS products. Potential enhancements to DMS are investigated including the use of ancillary terrain data. Finally, the impact of using sharpened LST, as input to a two-source energy balance model, on simulated ET will be evaluated. The ability to accurately monitor field-scale changes in vegetation cover, crop conditions and surface fluxes, are of main importance towards an efficient water use in areas where fresh water resources are scarce and poorly

RESEARCH OF REGISTRATION APPROACHES OF THERMAL INFRARED IMAGES AND INTENSITY IMAGES OF POINT CLOUD

Directory of Open Access Journals (Sweden)

L. Liu

2017-09-01

Full Text Available In order to realize the analysis of thermal energy of the objects in 3D vision, the registration approach of thermal infrared images and TLS (Terrestrial Laser Scanner point cloud was studied. The original data was pre-processed. For the sake of making the scale and brightness contrast of the two kinds of data meet the needs of basic matching, the intensity image of point cloud was produced and projected to spherical coordinate system, histogram equalization processing was done for thermal infrared image.This paper focused on the research of registration approaches of thermal infrared images and intensity images of point cloud based on SIFT，EOH-SIFT and PIIFD operators. The latter of which is usually used for medical image matching with different spectral character. The comparison results of the experiments showed that PIIFD operator got much more accurate feature point correspondences compared to SIFT and EOH-SIFT operators. The thermal infrared image and intensity image also have ideal overlap results by quadratic polynomial transformation. Therefore, PIIFD can be used as the basic operator for the registration of thermal infrared images and intensity images, and the operator can also be further improved by incorporating the iteration method.

Response of Turkey Muscle Satellite Cells to Thermal Challenge. II. Transcriptome Effects in Differentiating Cells

Directory of Open Access Journals (Sweden)

Kent M. Reed

2017-11-01

Full Text Available Background: Exposure of poultry to extreme temperatures during the critical period of post-hatch growth can seriously affect muscle development and thus compromise subsequent meat quality. This study was designed to characterize transcriptional changes induced in turkey muscle satellite cells by thermal challenge during differentiation. Our goal is to better define how thermal stress alters breast muscle ultrastructure and subsequent development.Results: Skeletal muscle satellite cells previously isolated from the Pectoralis major muscle of 7-wk-old male turkeys (Meleagris gallopavo from two breeding lines: the F-line (16 wk body weight-selected and RBC2 (randombred control line were used in this study. Cultured cells were induced to differentiate at 38°C (control or thermal challenge temperatures of 33 or 43°C. After 48 h of differentiation, cells were harvested and total RNA was isolated for RNAseq analysis. Analysis of 39.9 Gb of sequence found 89% mapped to the turkey genome (UMD5.0, annotation 101 with average expression of 18,917 genes per library. In the cultured satellite cells, slow/cardiac muscle isoforms are generally present in greater abundance than fast skeletal isoforms. Statistically significant differences in gene expression were observed among treatments and between turkey lines, with a greater number of genes affected in the F-line cells following cold treatment whereas more differentially expressed (DE genes were observed in the RBC2 cells following heat treatment. Many of the most significant pathways involved signaling, consistent with ongoing cellular differentiation. Regulation of Ca2+ homeostasis appears to be significantly affected by temperature treatment, particularly cold treatment.Conclusions: Satellite cell differentiation is directly influenced by temperature at the level of gene transcription with greater effects attributed to selection for fast growth. At lower temperature, muscle-associated genes in the

Research on Space Environmental Effect of Organic Composite Materials for Thermal Management of Satellites Using MC-50 Cyclotron

Directory of Open Access Journals (Sweden)

Dae-Weon Kim

2005-12-01

Full Text Available The organic material is one of the most popular material for the satellites and the spacecrafts in order to perform the thermal management, and to protect direct exposure from the space environment. The present paper observes material property changes of organic material under the space environment by using ground facilities. One of the representative organic thermal management material of satellites, 2 mil ITO(Indium Tin Oxide coated aluminized KAPTON was selected for experiments. In order to investigate the single parametric effect of protons in space environment, MC-50 cyclotron system in KIRAMS(Korea Institute of Radiological and Medical Science was utilized for the ion beam irradiation of protons and ion beam dose was set to the Very Large August 1972 EVENT model, the highest protons occurrence near the earth orbit in history. The energy of ion beam is fixed to 30MeV(mega electron volt, observed average energy, and the equivalent irradiance time conditions were set to 1-year, 3-year, 5-year and 10-year exposure in space. The procedure of analyses includes the measurement of the ultimate tensile strength for the assessment of quantitative degradation in material properties, and the imaging analyses of crystalline transformation and damages on the exposed surface by FE-SEM(Field Emission Scanning Electron Spectroscopy etc.

A novel technique to monitor thermal discharges using thermal infrared imaging.

Science.gov (United States)

Muthulakshmi, A L; Natesan, Usha; Ferrer, Vincent A; Deepthi, K; Venugopalan, V P; Narasimhan, S V

2013-09-01

Coastal temperature is an important indicator of water quality, particularly in regions where delicate ecosystems sensitive to water temperature are present. Remote sensing methods are highly reliable for assessing the thermal dispersion. The plume dispersion from the thermal outfall of the nuclear power plant at Kalpakkam, on the southeast coast of India, was investigated from March to December 2011 using thermal infrared images along with field measurements. The absolute temperature as provided by the thermal infrared (TIR) images is used in the Arc GIS environment for generating a spatial pattern of the plume movement. Good correlation of the temperature measured by the TIR camera with the field data (r(2) = 0.89) make it a reliable method for the thermal monitoring of the power plant effluents. The study portrays that the remote sensing technique provides an effective means of monitoring the thermal distribution pattern in coastal waters.

Adapting Local Features for Face Detection in Thermal Image

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Chao Ma

2017-11-01

Full Text Available A thermal camera captures the temperature distribution of a scene as a thermal image. In thermal images, facial appearances of different people under different lighting conditions are similar. This is because facial temperature distribution is generally constant and not affected by lighting condition. This similarity in face appearances is advantageous for face detection. To detect faces in thermal images, cascade classifiers with Haar-like features are generally used. However, there are few studies exploring the local features for face detection in thermal images. In this paper, we introduce two approaches relying on local features for face detection in thermal images. First, we create new feature types by extending Multi-Block LBP. We consider a margin around the reference and the generally constant distribution of facial temperature. In this way, we make the features more robust to image noise and more effective for face detection in thermal images. Second, we propose an AdaBoost-based training method to get cascade classifiers with multiple types of local features. These feature types have different advantages. In this way we enhance the description power of local features. We did a hold-out validation experiment and a field experiment. In the hold-out validation experiment, we captured a dataset from 20 participants, comprising 14 males and 6 females. For each participant, we captured 420 images with 10 variations in camera distance, 21 poses, and 2 appearances (participant with/without glasses. We compared the performance of cascade classifiers trained by different sets of the features. The experiment results showed that the proposed approaches effectively improve the performance of face detection in thermal images. In the field experiment, we compared the face detection performance in realistic scenes using thermal and RGB images, and gave discussion based on the results.

On the relationship between satellite-estimated bio-optical and thermal properties in the Gulf of Mexico

Science.gov (United States)

Jolliff, Jason K.; Kindle, John C.; Penta, Bradley; Helber, Robert; Lee, Zhongping; Shulman, Igor; Arnone, Robert; Rowley, Clark D.

2008-03-01

Three years of Sea-viewing Wide Field-of-view Sensor (SeaWiFS) ocean color data were combined with three-dimensional thermal fields generated by the U.S. Navy's Modular Ocean Data Assimilation System (MODAS) in order to examine the interdependencies between bio-optical fields and their relationship to seasonal and mesoscale changes in upper ocean thermal structure. The combined data set suggests that the oceanic boundary layer within the Gulf of Mexico may be broadly defined by two seasonally occurring bio-thermal periods. A winter mixing period, characterized by net heat losses to the atmosphere, deepening of the isothermal layer depth, and annual maxima of satellite-estimated colored detrital matter (CDM) absorption coefficients and surface pigment concentration, was followed by a thermally stratified period characterized by net surface ocean heating, reduced isothermal layer depths, and annual minima in surface bio-optical fields. Variability in the interdependencies of ocean color products was used to diagnose an attendant shift in the size-structure of surface phytoplankton communities as well as identify CDM as the constituent responsible for the majority of blue-light absorption in Gulf of Mexico surface waters. The mesoscale circulation, as resolved by MODAS thermal fields into cold and warm-core eddies, appears to significantly modulate the seasonal bio-optical cycle of CDM absorption and surface pigment concentration. An empirical model was developed to describe CDM absorption as a function of upper ocean thermal energy. The model accounted for nearly half the variance in the satellite-estimate of this bio-optical variable. Large mismatches between the model and satellite data implied episodes of shelf water export to the deep Gulf of Mexico.

Estimating envelope thermal characteristics from single point in time thermal images

Science.gov (United States)

Alshatshati, Salahaldin Faraj

Energy efficiency programs implemented nationally in the U.S. by utilities have rendered savings which have cost on average 0.03/kWh. This cost is still well below generation costs. However, as the lowest cost energy efficiency measures are adopted, this the cost effectiveness of further investment declines. Thus there is a need to more effectively find the most opportunities for savings regionally and nationally, so that the greatest cost effectiveness in implementing energy efficiency can be achieved. Integral to this process. are at scale energy audits. However, on-site building energy audits process are expensive, in the range of US1.29/m2-$5.37/m2 and there are an insufficient number of professionals to perform the audits. Energy audits that can be conducted at-scale and at low cost are needed. Research is presented that addresses at community-wide scales characterization of building envelope thermal characteristics via drive-by and fly-over GPS linked thermal imaging. A central question drives this research: Can single point-in-time thermal images be used to infer U-values and thermal capacitances of walls and roofs? Previous efforts to use thermal images to estimate U-values have been limited to rare steady exterior weather conditions. The approaches posed here are based upon the development two models first is a dynamic model of a building envelope component with unknown U-value and thermal capacitance. The weather conditions prior to the thermal image are used as inputs to the model. The model is solved to determine the exterior surface temperature, ultimately predicted the temperature at the thermal measurement time. The model U-value and thermal capacitance are tuned in order to force the error between the predicted surface temperature and the measured surface temperature from thermal imaging to be near zero. This model is developed simply to show that such a model cannot be relied upon to accurately estimate the U-value. The second is a data

Geostationary Satellite (GOES) Images

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Visible and Infrared satellite imagery taken from radiometer instruments on SMS (ATS) and GOES satellites in geostationary orbit. These satellites produced...

Autonomous Planetary 3-D Reconstruction From Satellite Images

DEFF Research Database (Denmark)

Denver, Troelz

1999-01-01

is discussed.Based on such features, 3-D representations may be compiled from two or more 2-D satellite images. The main purposes of such a mapping system are extraction of landing sites, objects of scientific interest and general planetary surveying. All data processing is performed autonomously onboard...

AUTOMATIC CLOUD DETECTION FROM MULTI-TEMPORAL SATELLITE IMAGES: TOWARDS THE USE OF PLÉIADES TIME SERIES

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N. Champion

2012-08-01

Full Text Available Contrary to aerial images, satellite images are often affected by the presence of clouds. Identifying and removing these clouds is one of the primary steps to perform when processing satellite images, as they may alter subsequent procedures such as atmospheric corrections, DSM production or land cover classification. The main goal of this paper is to present the cloud detection approach, developed at the French Mapping agency. Our approach is based on the availability of multi-temporal satellite images (i.e. time series that generally contain between 5 and 10 images and is based on a region-growing procedure. Seeds (corresponding to clouds are firstly extracted through a pixel-to-pixel comparison between the images contained in time series (the presence of a cloud is here assumed to be related to a high variation of reflectance between two images. Clouds are then delineated finely using a dedicated region-growing algorithm. The method, originally designed for panchromatic SPOT5-HRS images, is tested in this paper using time series with 9 multi-temporal satellite images. Our preliminary experiments show the good performances of our method. In a near future, the method will be applied to Pléiades images, acquired during the in-flight commissioning phase of the satellite (launched at the end of 2011. In that context, this is a particular goal of this paper to show to which extent and in which way our method can be adapted to this kind of imagery.

Using Sentinel-1 and Landsat 8 satellite images to estimate surface soil moisture content.

Science.gov (United States)

Mexis, Philippos-Dimitrios; Alexakis, Dimitrios D.; Daliakopoulos, Ioannis N.; Tsanis, Ioannis K.

2016-04-01

Nowadays, the potential for more accurate assessment of Soil Moisture (SM) content exploiting Earth Observation (EO) technology, by exploring the use of synergistic approaches among a variety of EO instruments has emerged. This study is the first to investigate the potential of Synthetic Aperture Radar (SAR) (Sentinel-1) and optical (Landsat 8) images in combination with ground measurements to estimate volumetric SM content in support of water management and agricultural practices. SAR and optical data are downloaded and corrected in terms of atmospheric, geometric and radiometric corrections. SAR images are also corrected in terms of roughness and vegetation with the synergistic use of Oh and Topp models using a dataset consisting of backscattering coefficients and corresponding direct measurements of ground parameters (moisture, roughness). Following, various vegetation indices (NDVI, SAVI, MSAVI, EVI, etc.) are estimated to record diachronically the vegetation regime within the study area and as auxiliary data in the final modeling. Furthermore, thermal images from optical data are corrected and incorporated to the overall approach. The basic principle of Thermal InfraRed (TIR) method is that Land Surface Temperature (LST) is sensitive to surface SM content due to its impact on surface heating process (heat capacity and thermal conductivity) under bare soil or sparse vegetation cover conditions. Ground truth data are collected from a Time-domain reflectometer (TRD) gauge network established in western Crete, Greece, during 2015. Sophisticated algorithms based on Artificial Neural Networks (ANNs) and Multiple Linear Regression (MLR) approaches are used to explore the statistical relationship between backscattering measurements and SM content. Results highlight the potential of SAR and optical satellite images to contribute to effective SM content detection in support of water resources management and precision agriculture. Keywords: Sentinel-1, Landsat 8, Soil

Geomorphology of coastal environments from satellite images

International Nuclear Information System (INIS)

Da Rocha Ribeiro, R.; Velho, L.; Schossler, V.

2010-01-01

This study aims at recognizing coastal environments supported by data from the Landsat Thematic Mapper (TM) satellite. The digital processing of images, System Information Geographic (SIG) techniques and field observation in one section of the “Província Costeira do Rio Grande do Sul” between the Rio Grande and the São Gonçalo channels - resulted in a geomorphologic profile and mapping

Development of a Lyman-α Imaging Solar Telescope for the Satellite

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M. Jang

2005-09-01

Full Text Available Long term observations of full-disk Lyman-α irradiance have been made by the instruments on various satellites. In addition, several sounding rockets dating back to the 1950s and up through the present have measured the Lyman-α irradiance. Previous full disk Lyman-α images of the sun have been very interesting and useful scientifically, but have been only five-minute ``snapshots" obtained on sounding rocket flights. All of these observations to date have been snapshots, with no time resolution to observe changes in the chromospheric structure as a result of the evolving magnetic field, and its effect on the Lyman-α intensity. The Lyman-α Imaging Solar Telescope(LIST can provide a unique opportunity for the study of the sun in the Lyman-α region with the high time and spatial resolution for the first time. Up to the 2nd year development, the preliminary design of the optics, mechanical structure and electronics system has been completed. Also the mechanical structure analysis, thermal analysis were performed and the material for the structure was chosen as a result of these analyses. And the test plan and the verification matrix were decided. The operation systems, technical and scientific operation, were studied and finally decided. Those are the technical operation, mechanical working modes for the observation and safety, the scientific operation and the process of the acquired data. The basic techniques acquired through the development of satellite based solar telescope are essential for the construction of space environment forecast system in the future. The techniques which we developed through this study, like mechanical, optical and data processing techniques, could be applied extensively not only to the process of the future production of flight models of this kind, but also to the related industries. Also, we can utilize the scientific achievements which are obtained throughout the project. And these can be utilized to build a high

Electron-beam-welded segmental heat pipes of AlMgSi 1 for the thermal model of the satellite Aeros-A

Energy Technology Data Exchange (ETDEWEB)

Hoell, H.; Lasar, H.

1974-07-01

For the purposes of tests with the thermal model of the German aeronomy satellite Aeros-A, a heat pipe system of optimized weight was developed in order to transport thermal energy from the solar cells of the cylindrical satellite to the conical bottom. Because of stringent requirements on the fabrication process, electron beam welding is used for bonding. The welding process is described and preliminary test results are given. (LEW)

Uncertainty Evaluations of the CRCS In-orbit Field Radiometric Calibration Methods for Thermal Infrared Channels of FENGYUN Meteorological Satellites

Science.gov (United States)

Zhang, Y.; Rong, Z.; Min, M.; Hao, X.; Yang, H.

2017-12-01

Meteorological satellites have become an irreplaceable weather and ocean-observing tool in China. These satellites are used to monitor natural disasters and improve the efficiency of many sectors of Chinese national economy. It is impossible to ignore the space-derived data in the fields of meteorology, hydrology, and agriculture, as well as disaster monitoring in China, a large agricultural country. For this reason, China is making a sustained effort to build and enhance its meteorological observing system and application system. The first Chinese polar-orbiting weather satellite was launched in 1988. Since then China has launched 14 meteorological satellites, 7 of which are sun synchronous and 7 of which are geostationary satellites; China will continue its two types of meteorological satellite programs. In order to achieve the in-orbit absolute radiometric calibration of the operational meteorological satellites' thermal infrared channels, China radiometric calibration sites (CRCS) established a set of in-orbit field absolute radiometric calibration methods (FCM) for thermal infrared channels (TIR) and the uncertainty of this method was evaluated and analyzed based on TERRA/AQUA MODIS observations. Comparisons between the MODIS at pupil brightness temperatures (BTs) and the simulated BTs at the top of atmosphere using radiative transfer model (RTM) based on field measurements showed that the accuracy of the current in-orbit field absolute radiometric calibration methods was better than 1.00K (@300K, K=1) in thermal infrared channels. Therefore, the current CRCS field calibration method for TIR channels applied to Chinese metrological satellites was with favorable calibration accuracy: for 10.5-11.5µm channel was better than 0.75K (@300K, K=1) and for 11.5-12.5µm channel was better than 0.85K (@300K, K=1).

Remote diagnosis via a telecommunication satellite--ultrasonic tomographic image transmission experiments.

Science.gov (United States)

Nakajima, I; Inokuchi, S; Tajima, T; Takahashi, T

1985-04-01

An experiment to transmit ultrasonic tomographic section images required for remote medical diagnosis and care was conducted using the mobile telecommunication satellite OSCAR-10. The images received showed the intestinal condition of a patient incapable of verbal communication, however the image screen had a fairly coarse particle structure. On the basis of these experiments, were considered as the transmission of ultrasonic tomographic images extremely effective in remote diagnosis.

Thermal Infrared Imaging-Based Computational Psychophysiology for Psychometrics.

Science.gov (United States)

Cardone, Daniela; Pinti, Paola; Merla, Arcangelo

2015-01-01

Thermal infrared imaging has been proposed as a potential system for the computational assessment of human autonomic nervous activity and psychophysiological states in a contactless and noninvasive way. Through bioheat modeling of facial thermal imagery, several vital signs can be extracted, including localized blood perfusion, cardiac pulse, breath rate, and sudomotor response, since all these parameters impact the cutaneous temperature. The obtained physiological information could then be used to draw inferences about a variety of psychophysiological or affective states, as proved by the increasing number of psychophysiological studies using thermal infrared imaging. This paper presents therefore a review of the principal achievements of thermal infrared imaging in computational physiology with regard to its capability of monitoring psychophysiological activity.

An Improved Image Encryption Algorithm Based on Cyclic Rotations and Multiple Chaotic Sequences: Application to Satellite Images

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MADANI Mohammed

2017-10-01

Full Text Available In this paper, a new satellite image encryption algorithm based on the combination of multiple chaotic systems and a random cyclic rotation technique is proposed. Our contribution consists in implementing three different chaotic maps (logistic, sine, and standard combined to improve the security of satellite images. Besides enhancing the encryption, the proposed algorithm also focuses on advanced efficiency of the ciphered images. Compared with classical encryption schemes based on multiple chaotic maps and the Rubik's cube rotation, our approach has not only the same merits of chaos systems like high sensitivity to initial values, unpredictability, and pseudo-randomness, but also other advantages like a higher number of permutations, better performances in Peak Signal to Noise Ratio (PSNR and a Maximum Deviation (MD.

Satellite Remote Sensing in Seismology. A Review

Directory of Open Access Journals (Sweden)

Andrew A. Tronin

2009-12-01

Full Text Available A wide range of satellite methods is applied now in seismology. The first applications of satellite data for earthquake exploration were initiated in the ‘70s, when active faults were mapped on satellite images. It was a pure and simple extrapolation of airphoto geological interpretation methods into space. The modern embodiment of this method is alignment analysis. Time series of alignments on the Earth's surface are investigated before and after the earthquake. A further application of satellite data in seismology is related with geophysical methods. Electromagnetic methods have about the same long history of application for seismology. Stable statistical estimations of ionosphere-lithosphere relation were obtained based on satellite ionozonds. The most successful current project "DEMETER" shows impressive results. Satellite thermal infra-red data were applied for earthquake research in the next step. Numerous results have confirmed previous observations of thermal anomalies on the Earth's surface prior to earthquakes. A modern trend is the application of the outgoing long-wave radiation for earthquake research. In ‘80s a new technology—satellite radar interferometry—opened a new page. Spectacular pictures of co-seismic deformations were presented. Current researches are moving in the direction of pre-earthquake deformation detection. GPS technology is also widely used in seismology both for ionosphere sounding and for ground movement detection. Satellite gravimetry has demonstrated its first very impressive results on the example of the catastrophic Indonesian earthquake in 2004. Relatively new applications of remote sensing for seismology as atmospheric sounding, gas observations, and cloud analysis are considered as possible candidates for applications.

An Investigation on Water Quality of Darlik Dam Drinking Water using Satellite Images

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Erhan Alparslan

2010-01-01

Full Text Available Darlik Dam supplies 15% of the water demand of Istanbul Metropolitan City of Turkey. Water quality (WQ in the Darlik Dam was investigated from Landsat 5 TM satellite images of the years 2004, 2005, and 2006 in order to determine land use/land cover changes in the watershed of the dam that may deteriorate its WQ. The images were geometrically and atmospherically corrected for WQ analysis. Next, an investigation was made by multiple regression analysis between the unitless planetary reflectance values of the first four bands of the June 2005 Landsat TM image of the dam and WQ parameters, such as chlorophyll-a, total dissolved matter, turbidity, total phosphorous, and total nitrogen, measured at satellite image acquisition time at seven stations in the dam. Finally, WQ in the dam was studied from satellite images of the years 2004, 2005, and 2006 by pattern recognition techniques in order to determine possible water pollution in the dam. This study was compared to a previous study done by the authors in the Küçükçekmece water reservoir, also in Istanbul City.

Automatic Registration Method for Fusion of ZY-1-02C Satellite Images

Directory of Open Access Journals (Sweden)

Qi Chen

2013-12-01

Full Text Available Automatic image registration (AIR has been widely studied in the fields of medical imaging, computer vision, and remote sensing. In various cases, such as image fusion, high registration accuracy should be achieved to meet application requirements. For satellite images, the large image size and unstable positioning accuracy resulting from the limited manufacturing technology of charge-coupled device, focal plane distortion, and unrecorded spacecraft jitter lead to difficulty in obtaining agreeable corresponding points for registration using only area-based matching or feature-based matching. In this situation, a coarse-to-fine matching strategy integrating two types of algorithms is proven feasible and effective. In this paper, an AIR method for application to the fusion of ZY-1-02C satellite imagery is proposed. First, the images are geometrically corrected. Coarse matching, based on scale invariant feature transform, is performed for the subsampled corrected images, and a rough global estimation is made with the matching results. Harris feature points are then extracted, and the coordinates of the corresponding points are calculated according to the global estimation results. Precise matching is conducted, based on normalized cross correlation and least squares matching. As complex image distortion cannot be precisely estimated, a local estimation using the structure of triangulated irregular network is applied to eliminate the false matches. Finally, image resampling is conducted, based on local affine transformation, to achieve high-precision registration. Experiments with ZY-1-02C datasets demonstrate that the accuracy of the proposed method meets the requirements of fusion application, and its efficiency is also suitable for the commercial operation of the automatic satellite data process system.

Automatic Detection of Clouds and Shadows Using High Resolution Satellite Image Time Series

Science.gov (United States)

Champion, Nicolas

2016-06-01

Detecting clouds and their shadows is one of the primaries steps to perform when processing satellite images because they may alter the quality of some products such as large-area orthomosaics. The main goal of this paper is to present the automatic method developed at IGN-France for detecting clouds and shadows in a sequence of satellite images. In our work, surface reflectance orthoimages are used. They were processed from initial satellite images using a dedicated software. The cloud detection step consists of a region-growing algorithm. Seeds are firstly extracted. For that purpose and for each input ortho-image to process, we select the other ortho-images of the sequence that intersect it. The pixels of the input ortho-image are secondly labelled seeds if the difference of reflectance (in the blue channel) with overlapping ortho-images is bigger than a given threshold. Clouds are eventually delineated using a region-growing method based on a radiometric and homogeneity criterion. Regarding the shadow detection, our method is based on the idea that a shadow pixel is darker when comparing to the other images of the time series. The detection is basically composed of three steps. Firstly, we compute a synthetic ortho-image covering the whole study area. Its pixels have a value corresponding to the median value of all input reflectance ortho-images intersecting at that pixel location. Secondly, for each input ortho-image, a pixel is labelled shadows if the difference of reflectance (in the NIR channel) with the synthetic ortho-image is below a given threshold. Eventually, an optional region-growing step may be used to refine the results. Note that pixels labelled clouds during the cloud detection are not used for computing the median value in the first step; additionally, the NIR input data channel is used to perform the shadow detection, because it appeared to better discriminate shadow pixels. The method was tested on times series of Landsat 8 and Pl

AUTOMATIC DETECTION OF CLOUDS AND SHADOWS USING HIGH RESOLUTION SATELLITE IMAGE TIME SERIES

Directory of Open Access Journals (Sweden)

N. Champion

2016-06-01

Full Text Available Detecting clouds and their shadows is one of the primaries steps to perform when processing satellite images because they may alter the quality of some products such as large-area orthomosaics. The main goal of this paper is to present the automatic method developed at IGN-France for detecting clouds and shadows in a sequence of satellite images. In our work, surface reflectance orthoimages are used. They were processed from initial satellite images using a dedicated software. The cloud detection step consists of a region-growing algorithm. Seeds are firstly extracted. For that purpose and for each input ortho-image to process, we select the other ortho-images of the sequence that intersect it. The pixels of the input ortho-image are secondly labelled seeds if the difference of reflectance (in the blue channel with overlapping ortho-images is bigger than a given threshold. Clouds are eventually delineated using a region-growing method based on a radiometric and homogeneity criterion. Regarding the shadow detection, our method is based on the idea that a shadow pixel is darker when comparing to the other images of the time series. The detection is basically composed of three steps. Firstly, we compute a synthetic ortho-image covering the whole study area. Its pixels have a value corresponding to the median value of all input reflectance ortho-images intersecting at that pixel location. Secondly, for each input ortho-image, a pixel is labelled shadows if the difference of reflectance (in the NIR channel with the synthetic ortho-image is below a given threshold. Eventually, an optional region-growing step may be used to refine the results. Note that pixels labelled clouds during the cloud detection are not used for computing the median value in the first step; additionally, the NIR input data channel is used to perform the shadow detection, because it appeared to better discriminate shadow pixels. The method was tested on times series of Landsat 8

Method and apparatus for implementing material thermal property measurement by flash thermal imaging

Science.gov (United States)

Sun, Jiangang

2017-11-14

A method and apparatus are provided for implementing measurement of material thermal properties including measurement of thermal effusivity of a coating and/or film or a bulk material of uniform property. The test apparatus includes an infrared camera, a data acquisition and processing computer coupled to the infrared camera for acquiring and processing thermal image data, a flash lamp providing an input of heat onto the surface of a two-layer sample with an enhanced optical filter covering the flash lamp attenuating an entire infrared wavelength range with a series of thermal images is taken of the surface of the two-layer sample.

Global Solar Radiation in Spain from Satellite Images

International Nuclear Information System (INIS)

Ramirez, L.; Mora, L.; Sidrach de Cardona, M.; Navarro, A. A.; Varela, M.; Cruz, M. de la

2003-01-01

In the context of the present work a series of algorithms of calculation of the solar radiation from satellite images has been developed. These models, have been applied to three years of images of the Meteosat satellite and the results of the treatment have been extrapolated to long term. For the development of the models of solar radiation registered in ground stations have been used, corresponding all of them to localities of peninsular Spain and the Balearic ones. The maximum periods of data available have been used, supposing in most of the cases periods of between 6 and 9 years. From the results has a year type of images of global solar radiation on horizontal surface. The original resolution of the image of 7x7 km in the study latitudes, has been reevaluated to 5x5 km. This supposes to have a value of the typical radiation for every day of the year, each 5x5 km in the study territory. This information, supposes an important advance as far as the knowledge of the space distribution of the radiation solar, impossible to reach about alternative methods. Doubtlessly, the precision of the provided values is not comparable with pyrano metric measures in a concrete locality, but it provides a very valid indicator in places in which it is not had previous information. In addition to the radiation maps, tables of the global solar radiation have been prepared on different inclinations, from the global radiation on horizontal surface calculated for every day of the year and in each pixel of the image. (Author) 24 refs

AUTOMATED CONSTRUCTION OF COVERAGE CATALOGUES OF ASTER SATELLITE IMAGE FOR URBAN AREAS OF THE WORLD

Directory of Open Access Journals (Sweden)

H. Miyazaki

2012-07-01

Full Text Available We developed an algorithm to determine a combination of satellite images according to observation extent and image quality. The algorithm was for testing necessity for completing coverage of the search extent. The tests excluded unnecessary images with low quality and preserve necessary images with good quality. The search conditions of the satellite images could be extended, indicating the catalogue could be constructed with specified periods required for time series analysis. We applied the method to a database of metadata of ASTER satellite images archived in GEO Grid of National Institute of Advanced Industrial Science and Technology (AIST, Japan. As indexes of populated places with geographical coordinates, we used a database of 3372 populated place of more than 0.1 million populations retrieved from GRUMP Settlement Points, a global gazetteer of cities, which has geographical names of populated places associated with geographical coordinates and population data. From the coordinates of populated places, 3372 extents were generated with radiuses of 30 km, a half of swath of ASTER satellite images. By merging extents overlapping each other, they were assembled into 2214 extents. As a result, we acquired combinations of good quality for 1244 extents, those of low quality for 96 extents, incomplete combinations for 611 extents. Further improvements would be expected by introducing pixel-based cloud assessment and pixel value correction over seasonal variations.

Performance Evaluation Facility for Fire Fighting Thermal Imager

International Nuclear Information System (INIS)

Kim, Sung Chan; Amon, Francine; Hamins, Anthony

2007-01-01

The present study investigates the characteristics of obscuring media inside an optical smoke cell, which is a bench-scale testing facility for the evaluation of thermal imaging cameras used by fire fighters. Light extinction coefficient and visibility through the smoke cell is characterized by the measured laser transmittance. The laser transmittance along the axial direction of the smoke cell is relatively uniform at upper and lower part for various air/fuel volume flow rate. Contrast level based image quality of visible CCD camera through the smoke cell is compared with that of thermal imaging camera. The optical smoke cell can be used as well-controlled and effective laboratory-scale test apparatus to evaluate the performance of thermal imaging camera for fire fighting application

V-SIPAL - A VIRTUAL LABORATORY FOR SATELLITE IMAGE PROCESSING AND ANALYSIS

Directory of Open Access Journals (Sweden)

K. M. Buddhiraju

2012-09-01

Full Text Available In this paper a virtual laboratory for the Satellite Image Processing and Analysis (v-SIPAL being developed at the Indian Institute of Technology Bombay is described. v-SIPAL comprises a set of experiments that are normally carried out by students learning digital processing and analysis of satellite images using commercial software. Currently, the experiments that are available on the server include Image Viewer, Image Contrast Enhancement, Image Smoothing, Edge Enhancement, Principal Component Transform, Texture Analysis by Co-occurrence Matrix method, Image Indices, Color Coordinate Transforms, Fourier Analysis, Mathematical Morphology, Unsupervised Image Classification, Supervised Image Classification and Accuracy Assessment. The virtual laboratory includes a theory module for each option of every experiment, a description of the procedure to perform each experiment, the menu to choose and perform the experiment, a module on interpretation of results when performed with a given image and pre-specified options, bibliography, links to useful internet resources and user-feedback. The user can upload his/her own images for performing the experiments and can also reuse outputs of one experiment in another experiment where applicable. Some of the other experiments currently under development include georeferencing of images, data fusion, feature evaluation by divergence andJ-M distance, image compression, wavelet image analysis and change detection. Additions to the theory module include self-assessment quizzes, audio-video clips on selected concepts, and a discussion of elements of visual image interpretation. V-SIPAL is at the satge of internal evaluation within IIT Bombay and will soon be open to selected educational institutions in India for evaluation.

Quantitative assessment of pain-related thermal dysfunction through clinical digital infrared thermal imaging

Directory of Open Access Journals (Sweden)

Frize Monique

2004-06-01

Full Text Available Abstract Background The skin temperature distribution of a healthy human body exhibits a contralateral symmetry. Some nociceptive and most neuropathic pain pathologies are associated with an alteration of the thermal distribution of the human body. Since the dissipation of heat through the skin occurs for the most part in the form of infrared radiation, infrared thermography is the method of choice to study the physiology of thermoregulation and the thermal dysfunction associated with pain. Assessing thermograms is a complex and subjective task that can be greatly facilitated by computerised techniques. Methods This paper presents techniques for automated computerised assessment of thermal images of pain, in order to facilitate the physician's decision making. First, the thermal images are pre-processed to reduce the noise introduced during the initial acquisition and to extract the irrelevant background. Then, potential regions of interest are identified using fixed dermatomal subdivisions of the body, isothermal analysis and segmentation techniques. Finally, we assess the degree of asymmetry between contralateral regions of interest using statistical computations and distance measures between comparable regions. Results The wavelet domain-based Poisson noise removal techniques compared favourably against Wiener and other wavelet-based denoising methods, when qualitative criteria were used. It was shown to improve slightly the subsequent analysis. The automated background removal technique based on thresholding and morphological operations was successful for both noisy and denoised images with a correct removal rate of 85% of the images in the database. The automation of the regions of interest (ROIs delimitation process was achieved successfully for images with a good contralateral symmetry. Isothermal division complemented well the fixed ROIs division based on dermatomes, giving a more accurate map of potentially abnormal regions. The measure

Seeing is believing I: The use of thermal sensing from satellite imagery to predict crop yield

International Nuclear Information System (INIS)

Potgieter A B; Rodriguez D; Power B; Mclean J; Davis P

2014-01-01

Volatility in crop production has been part of the Australian environment since cropping began with the arrival of the first European settlers. Climate variability is the main factor affecting crop production at national, state and local scales. At field level spatial patterns on yield production are also determined by spatially changing soil properties in interaction with seasonal climate conditions and weather patterns at critical stages in the crop development. Here we used a combination of field level weather records, canopy characteristics, and satellite information to determine the spatial performance of a large field of wheat. The main objective of this research is to determine the ability of remote sensing technologies to capture yield losses due to water stress at the canopy level. The yield, canopy characteristics (i.e. canopy temperature and ground cover) and seasonal conditions of a field of wheat (∼1400ha) (-29.402° South and 149.508°, New South Wales, Australia) were continuously monitored during the winter of 2011. Weather and crop variables were continuously monitored by installing three automatic weather stations in a transect covering different positions and soils in the landscape. Weather variables included rainfall, minimum and maximum temperatures and relative humidity, and crop characteristics included ground cover and canopy temperature. Satellite imagery Landsat TM 5 and 7 was collected at five different stages in the crop cycle. Weather variables and crop characteristics were used to calculate a crop stress index (CSI) at point and field scale (39 fields). Field data was used to validate a spatial satellite image derived index. Spatial yield data was downloaded from the harvester at the different locations in the field. We used the thermal band (land surface temperature, LST) and enhanced vegetation index (EVI) bands from the MODIS (250 m for visible bands and 1km for thermal band) and a derived EVI from Landsat TM 7 (25 m for visible

Prospects of application of survey satellite image for meteorology

Science.gov (United States)

Kapochkina, A. B.; Kapochkin, B. B.; Kucherenko, N. V.

The maximal interest is represented with the information from geostationary satellites. These satellites repeat shootings the chosen territories, allowing to study dynamics of images. Most interesting shootings in IR a range. Studying of survey image is applied to studying linear elements of clouds (LEC). It is established, that "LEC " arise only above breaks of an earth's crust. In research results of the complex analysis of the satellite data, hydrometeorological supervision, seismicity, supervision over deformations of a surface of the Earth are used. It is established that before formation "LEC " in a ground layer arise anomalies of temperature and humidity. The situation above Europe 16 May, 2001 is considered. "LEC " in Europe block carry of air weights from the west to the east. Synoptic conditions above the Great Britain July, 7-10, 2000 is considered. Moving "LEC" trace distribution of deformation waves to an earth's crust. Satellite shootings Europe before earthquake in Greece 14.08.2003 are considered. These days ground supervision were conducted and the data of the geostationary satellite were analyzed. During moving "LEC " occur failures (destruction houses & of gas mains), earthquake. The situation above Iberian peninsula 12-16.11.2001 is considered. "LEC" arose before flooding in Europe. The situation before flooding in Germany June, 6-8, 2002 and flooding on the river Kuban June, 16-23, 2002 is considered. In case of occurrence of tectonic compression of an earth's crust there are "LEC ", tracer intensive movements of air upwards and downwards above negative and positive anomalies of the form of a terrestrial surface, accordingly. Such meteorological situations are dangerous to flights of aircraft, the fast gravitational anomalies influencing into orbits of movement of satellites trace. The situation above equatorial Atlantic 26.03.2003 years is considered. At tectonic compression of continental scale overcast covers the whole continents for more

Thermal particle image velocity estimation of fire plume flow

Science.gov (United States)

Xiangyang Zhou; Lulu Sun; Shankar Mahalingam; David R. Weise

2003-01-01

For the purpose of studying wildfire spread in living vegetation such as chaparral in California, a thermal particle image velocity (TPIV) algorithm for nonintrusively measuring flame gas velocities through thermal infrared (IR) imagery was developed. By tracing thermal particles in successive digital IR images, the TPIV algorithm can estimate the velocity field in a...

Satellite image time series simulation for environmental monitoring

Science.gov (United States)

Guo, Tao

2014-11-01

The performance of environmental monitoring heavily depends on the availability of consecutive observation data and it turns out an increasing demand in remote sensing community for satellite image data in the sufficient resolution with respect to both spatial and temporal requirements, which appear to be conflictive and hard to tune tradeoffs. Multiple constellations could be a solution if without concerning cost, and thus it is so far interesting but very challenging to develop a method which can simultaneously improve both spatial and temporal details. There are some research efforts to deal with the problem from various aspects, a type of approaches is to enhance the spatial resolution using techniques of super resolution, pan-sharpen etc. which can produce good visual effects, but mostly cannot preserve spectral signatures and result in losing analytical value. Another type is to fill temporal frequency gaps by adopting time interpolation, which actually doesn't increase informative context at all. In this paper we presented a novel method to generate satellite images in higher spatial and temporal details, which further enables satellite image time series simulation. Our method starts with a pair of high-low resolution data set, and then a spatial registration is done by introducing LDA model to map high and low resolution pixels correspondingly. Afterwards, temporal change information is captured through a comparison of low resolution time series data, and the temporal change is then projected onto high resolution data plane and assigned to each high resolution pixel referring the predefined temporal change patterns of each type of ground objects to generate a simulated high resolution data. A preliminary experiment shows that our method can simulate a high resolution data with a good accuracy. We consider the contribution of our method is to enable timely monitoring of temporal changes through analysis of low resolution images time series only, and usage of

Effects of Per-Pixel Variability on Uncertainties in Bathymetric Retrievals from High-Resolution Satellite Images

Directory of Open Access Journals (Sweden)

Elizabeth J. Botha

2016-05-01

Full Text Available Increased sophistication of high spatial resolution multispectral satellite sensors provides enhanced bathymetric mapping capability. However, the enhancements are counter-acted by per-pixel variability in sunglint, atmospheric path length and directional effects. This case-study highlights retrieval errors from images acquired at non-optimal geometrical combinations. The effects of variations in the environmental noise on water surface reflectance and the accuracy of environmental variable retrievals were quantified. Two WorldView-2 satellite images were acquired, within one minute of each other, with Image 1 placed in a near-optimal sun-sensor geometric configuration and Image 2 placed close to the specular point of the Bidirectional Reflectance Distribution Function (BRDF. Image 2 had higher total environmental noise due to increased surface glint and higher atmospheric path-scattering. Generally, depths were under-estimated from Image 2, compared to Image 1. A partial improvement in retrieval error after glint correction of Image 2 resulted in an increase of the maximum depth to which accurate depth estimations were returned. This case-study indicates that critical analysis of individual images, accounting for the entire sun elevation and azimuth and satellite sensor pointing and geometry as well as anticipated wave height and direction, is required to ensure an image is fit for purpose for aquatic data analysis.

Characterization of 3 to 5 Micron Thermal Imagers and Analysis of Narrow Band Images

National Research Council Canada - National Science Library

Quek, Yew S

2004-01-01

...) and the Minimum Resolvable Temperature (MRT). An available thermal imager, the Cincinnati Electronics IRRIS-256LN, and a newly purchased thermal imager, the Indigo Systems Merlin InSb Laboratory Camera, were investigated and compared...

Use of thermal infrared imaging for monitoring renewed dome growth at Mount St. Helens, 2004: Chapter 17 in A volcano rekindled: the renewed eruption of Mount St. Helens, 2004-2006

Science.gov (United States)

Schneider, David J.; Vallance, James W.; Wessels, Rick L.; Logan, Matthew; Ramsey, Michael S.; Sherrod, David R.; Scott, William E.; Stauffer, Peter H.

2008-01-01

A helicopter-mounted thermal imaging radiometer documented the explosive vent-clearing and effusive phases of the eruption of Mount St. Helens in 2004. A gyrostabilized gimbal controlled by a crew member housed the radiometer and an optical video camera attached to the nose of the helicopter. Since October 1, 2004, the system has provided thermal and video observations of dome growth. Flights conducted as frequently as twice daily during the initial month of the eruption monitored rapid changes in the crater and 1980-86 lava dome. Thermal monitoring decreased to several times per week once dome extrusion began. The thermal imaging system provided unique observations, including timely recognition that the early explosive phase was phreatic, location of structures controlling thermal emissions and active faults, detection of increased heat flow prior to the extrusion of lava, and recognition of new lava extrusion. The first spines, 1 and 2, were hotter when they emerged (maximum temperature 700-730°C) than subsequent spines insulated by as much as several meters of fault gouge. Temperature of gouge-covered spines was about 200°C where they emerged from the vent, and it decreased rapidly with distance from the vent. The hottest parts of these spines were as high as 500-730°C in fractured and broken-up regions. Such temperature variation needs to be accounted for in the retrieval of eruption parameters using satellite-based techniques, as such features are smaller than pixels in satellite images.

Moving object detection in video satellite image based on deep learning

Science.gov (United States)

Zhang, Xueyang; Xiang, Junhua

2017-11-01

Moving object detection in video satellite image is studied. A detection algorithm based on deep learning is proposed. The small scale characteristics of remote sensing video objects are analyzed. Firstly, background subtraction algorithm of adaptive Gauss mixture model is used to generate region proposals. Then the objects in region proposals are classified via the deep convolutional neural network. Thus moving objects of interest are detected combined with prior information of sub-satellite point. The deep convolution neural network employs a 21-layer residual convolutional neural network, and trains the network parameters by transfer learning. Experimental results about video from Tiantuo-2 satellite demonstrate the effectiveness of the algorithm.

SHADOW DETECTION FROM VERY HIGH RESOLUTON SATELLITE IMAGE USING GRABCUT SEGMENTATION AND RATIO-BAND ALGORITHMS

Directory of Open Access Journals (Sweden)

N. M. S. M. Kadhim

2015-03-01

Full Text Available Very-High-Resolution (VHR satellite imagery is a powerful source of data for detecting and extracting information about urban constructions. Shadow in the VHR satellite imageries provides vital information on urban construction forms, illumination direction, and the spatial distribution of the objects that can help to further understanding of the built environment. However, to extract shadows, the automated detection of shadows from images must be accurate. This paper reviews current automatic approaches that have been used for shadow detection from VHR satellite images and comprises two main parts. In the first part, shadow concepts are presented in terms of shadow appearance in the VHR satellite imageries, current shadow detection methods, and the usefulness of shadow detection in urban environments. In the second part, we adopted two approaches which are considered current state-of-the-art shadow detection, and segmentation algorithms using WorldView-3 and Quickbird images. In the first approach, the ratios between the NIR and visible bands were computed on a pixel-by-pixel basis, which allows for disambiguation between shadows and dark objects. To obtain an accurate shadow candidate map, we further refine the shadow map after applying the ratio algorithm on the Quickbird image. The second selected approach is the GrabCut segmentation approach for examining its performance in detecting the shadow regions of urban objects using the true colour image from WorldView-3. Further refinement was applied to attain a segmented shadow map. Although the detection of shadow regions is a very difficult task when they are derived from a VHR satellite image that comprises a visible spectrum range (RGB true colour, the results demonstrate that the detection of shadow regions in the WorldView-3 image is a reasonable separation from other objects by applying the GrabCut algorithm. In addition, the derived shadow map from the Quickbird image indicates

Shadow Detection from Very High Resoluton Satellite Image Using Grabcut Segmentation and Ratio-Band Algorithms

Science.gov (United States)

Kadhim, N. M. S. M.; Mourshed, M.; Bray, M. T.

2015-03-01

Very-High-Resolution (VHR) satellite imagery is a powerful source of data for detecting and extracting information about urban constructions. Shadow in the VHR satellite imageries provides vital information on urban construction forms, illumination direction, and the spatial distribution of the objects that can help to further understanding of the built environment. However, to extract shadows, the automated detection of shadows from images must be accurate. This paper reviews current automatic approaches that have been used for shadow detection from VHR satellite images and comprises two main parts. In the first part, shadow concepts are presented in terms of shadow appearance in the VHR satellite imageries, current shadow detection methods, and the usefulness of shadow detection in urban environments. In the second part, we adopted two approaches which are considered current state-of-the-art shadow detection, and segmentation algorithms using WorldView-3 and Quickbird images. In the first approach, the ratios between the NIR and visible bands were computed on a pixel-by-pixel basis, which allows for disambiguation between shadows and dark objects. To obtain an accurate shadow candidate map, we further refine the shadow map after applying the ratio algorithm on the Quickbird image. The second selected approach is the GrabCut segmentation approach for examining its performance in detecting the shadow regions of urban objects using the true colour image from WorldView-3. Further refinement was applied to attain a segmented shadow map. Although the detection of shadow regions is a very difficult task when they are derived from a VHR satellite image that comprises a visible spectrum range (RGB true colour), the results demonstrate that the detection of shadow regions in the WorldView-3 image is a reasonable separation from other objects by applying the GrabCut algorithm. In addition, the derived shadow map from the Quickbird image indicates significant performance of

Automated thermal mapping techniques using chromatic image analysis

Science.gov (United States)

Buck, Gregory M.

1989-01-01

Thermal imaging techniques are introduced using a chromatic image analysis system and temperature sensitive coatings. These techniques are used for thermal mapping and surface heat transfer measurements on aerothermodynamic test models in hypersonic wind tunnels. Measurements are made on complex vehicle configurations in a timely manner and at minimal expense. The image analysis system uses separate wavelength filtered images to analyze surface spectral intensity data. The system was initially developed for quantitative surface temperature mapping using two-color thermographic phosphors but was found useful in interpreting phase change paint and liquid crystal data as well.

IoSiS: a radar system for imaging of satellites in space

Science.gov (United States)

Jirousek, M.; Anger, S.; Dill, S.; Schreiber, E.; Peichl, M.

2017-05-01

Space debris nowadays is one of the main threats for satellite systems especially in low earth orbit (LEO). More than 700,000 debris objects with potential to destroy or damage a satellite are estimated. The effects of an impact often are not identifiable directly from ground. High-resolution radar images are helpful in analyzing a possible damage. Therefor DLR is currently developing a radar system called IoSiS (Imaging of Satellites in Space), being based on an existing steering antenna structure and our multi-purpose high-performance radar system GigaRad for experimental investigations. GigaRad is a multi-channel system operating at X band and using a bandwidth of up to 4.4 GHz in the IoSiS configuration, providing fully separated transmit (TX) and receive (RX) channels, and separated antennas. For the observation of small satellites or space debris a highpower traveling-wave-tube amplifier (TWTA) is mounted close to the TX antenna feed. For the experimental phase IoSiS uses a 9 m TX and a 1 m RX antenna mounted on a common steerable positioner. High-resolution radar images are obtained by using Inverse Synthetic Aperture Radar (ISAR) techniques. The guided tracking of known objects during overpass allows here wide azimuth observation angles. Thus high azimuth resolution comparable to the range resolution can be achieved. This paper outlines technical main characteristics of the IoSiS radar system including the basic setup of the antenna, the radar instrument with the RF error correction, and the measurement strategy. Also a short description about a simulation tool for the whole instrument and expected images is shown.

Thermal imaging for current D&S priorities

Science.gov (United States)

Craig, Robert; Parsons, John F.

2012-11-01

Supplying thermal imagers for today's operational needs requires flexibility, responsiveness and ever reducing costs. This paper will use the latest thermal imager development in the Catherine range from Thales UK to address the technical interactions with such issues as modularity, re-use, regions of deployment and supply chain management. All this is in the context of the increasingly public operations and the pressures on validating performance especially when weapon aiming is involved.

Discovering significant evolution patterns from satellite image time series.

Science.gov (United States)

Petitjean, François; Masseglia, Florent; Gançarski, Pierre; Forestier, Germain

2011-12-01

Satellite Image Time Series (SITS) provide us with precious information on land cover evolution. By studying these series of images we can both understand the changes of specific areas and discover global phenomena that spread over larger areas. Changes that can occur throughout the sensing time can spread over very long periods and may have different start time and end time depending on the location, which complicates the mining and the analysis of series of images. This work focuses on frequent sequential pattern mining (FSPM) methods, since this family of methods fits the above-mentioned issues. This family of methods consists of finding the most frequent evolution behaviors, and is actually able to extract long-term changes as well as short term ones, whenever the change may start and end. However, applying FSPM methods to SITS implies confronting two main challenges, related to the characteristics of SITS and the domain's constraints. First, satellite images associate multiple measures with a single pixel (the radiometric levels of different wavelengths corresponding to infra-red, red, etc.), which makes the search space multi-dimensional and thus requires specific mining algorithms. Furthermore, the non evolving regions, which are the vast majority and overwhelm the evolving ones, challenge the discovery of these patterns. We propose a SITS mining framework that enables discovery of these patterns despite these constraints and characteristics. Our proposal is inspired from FSPM and provides a relevant visualization principle. Experiments carried out on 35 images sensed over 20 years show the proposed approach makes it possible to extract relevant evolution behaviors.

Formation of the image on the receiver of thermal radiation

Science.gov (United States)

Akimenko, Tatiana A.

2018-04-01

The formation of the thermal picture of the observed scene with the verification of the quality of the thermal images obtained is one of the important stages of the technological process that determine the quality of the thermal imaging observation system. In this article propose to consider a model for the formation of a thermal picture of a scene, which must take into account: the features of the object of observation as the source of the signal; signal transmission through the physical elements of the thermal imaging system that produce signal processing at the optical, photoelectronic and electronic stages, which determines the final parameters of the signal and its compliance with the requirements for thermal information and measurement systems.

Laser-induced photo-thermal strain imaging

Science.gov (United States)

Choi, Changhoon; Ahn, Joongho; Jeon, Seungwan; Kim, Chulhong

2018-02-01

Vulnerable plaque is the one of the leading causes of cardiovascular disease occurrence. However, conventional intravascular imaging techniques suffer from difficulty in finding vulnerable plaque due to limitation such as lack of physiological information, imaging depth, and depth sensitivity. Therefore, new techniques are needed to help determine the vulnerability of plaque, Thermal strain imaging (TSI) is an imaging technique based on ultrasound (US) wave propagation speed that varies with temperature of medium. During temperature increase, strain occurs in the medium and its variation tendency is depending on the type of tissue, which makes it possible to use for tissue differentiation. Here, we demonstrate laser-induced photo-thermal strain imaging (pTSI) to differentiate tissue using an intravascular ultrasound (IVUS) catheter and a 1210-nm continuous-wave laser for heating lipids intensively. During heating, consecutive US images were obtained from a custom-made phantom made of porcine fat and gelatin. A cross correlation-based speckle-tracking algorithm was then applied to calculate the strain of US images. In the strain images, the positive strain produced in lipids (porcine fat) was clearly differentiated from water-bearing tissue (gelatin). This result shows that laser-induced pTSI could be a new method to distinguish lipids in the plaque and can help to differentiate vulnerability of plaque.

Framework of Jitter Detection and Compensation for High Resolution Satellites

Directory of Open Access Journals (Sweden)

Xiaohua Tong

2014-05-01

Full Text Available Attitude jitter is a common phenomenon in the application of high resolution satellites, which may result in large errors of geo-positioning and mapping accuracy. Therefore, it is critical to detect and compensate attitude jitter to explore the full geometric potential of high resolution satellites. In this paper, a framework of jitter detection and compensation for high resolution satellites is proposed and some preliminary investigation is performed. Three methods for jitter detection are presented as follows. (1 The first one is based on multispectral images using parallax between two different bands in the image; (2 The second is based on stereo images using rational polynomial coefficients (RPCs; (3 The third is based on panchromatic images employing orthorectification processing. Based on the calculated parallax maps, the frequency and amplitude of the detected jitter are obtained. Subsequently, two approaches for jitter compensation are conducted. (1 The first one is to conduct the compensation on image, which uses the derived parallax observations for resampling; (2 The second is to conduct the compensation on attitude data, which treats the influence of jitter on attitude as correction of charge-coupled device (CCD viewing angles. Experiments with images from several satellites, such as ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiaometer, LRO (Lunar Reconnaissance Orbiter and ZY-3 (ZiYuan-3 demonstrate the promising performance and feasibility of the proposed framework.

Thermal Imaging Systems for Real-Time Applications in Smart Cities

DEFF Research Database (Denmark)

Gade, Rikke; Moeslund, Thomas B.; Nielsen, Søren Zebitz

2016-01-01

of thermal imaging in real-time Smart City applications. Thermal cameras operate independently of light and measure the radiated infrared waves representing the temperature of the scene. In order to showcase the possibilities, we present five different applications which use thermal imaging only...

Foodstuff Survey Around a Major Nuclear Facility with Test of Satellite Image Application

International Nuclear Information System (INIS)

Fledderman, P.D.

1999-01-01

'A foodstuff survey was performed around the Savannah River Site, Aiken SC. It included a census of buildings and fields within 5 km of the boundary and determination of the locations and amounts of crops grown within 80 km of SRS center. Recent information for this region was collected on the amounts of meat, poultry, milk, and eggs produced, of deer hunted, and of sports fish caught. The locations and areas devoted to growing each crop were determined in two ways: by the usual process of assuming uniform crop distribution in each county on the basis of agricultural statistics reported by state agencies, and by analysis of two LANDSAT TM images obtained in May and September. For use with environmental radionuclide transfer and radiation dose calculation codes, locations within 80 km were defined for 64 sections by 16 sectors centered on the Site and by 16-km distance intervals from 16 km to 80 km. Most locally-raised foodstuff was distributed regionally and not retained locally for consumption. For four food crops, the amounts per section based on county agricultural statistics prorated by area were compared with the amounts per section based on satellite image analysis. The median ratios of the former to the latter were 0.6 - 0.7, suggesting that the two approaches are comparable but that satellite image analysis gave consistently higher amounts. Use of satellite image analysis is recommended on the basis of these findings to obtain site-specific, as compared to area-averaged, information on crop locations in conjunction with radionuclide pathway modelling. Some improvements in technique are suggested for satellite image application to characterize additional crops.'

Polar-Orbiting Satellite (POES) Images

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Visible and Infrared satellite imagery taken from camera systems or radiometer instruments on satellites in orbit around the poles. Satellite campaigns include...

3D reconstruction from multi-view VHR-satellite images in MicMac

Science.gov (United States)

Rupnik, Ewelina; Pierrot-Deseilligny, Marc; Delorme, Arthur

2018-05-01

This work addresses the generation of high quality digital surface models by fusing multiple depths maps calculated with the dense image matching method. The algorithm is adapted to very high resolution multi-view satellite images, and the main contributions of this work are in the multi-view fusion. The algorithm is insensitive to outliers, takes into account the matching quality indicators, handles non-correlated zones (e.g. occlusions), and is solved with a multi-directional dynamic programming approach. No geometric constraints (e.g. surface planarity) or auxiliary data in form of ground control points are required for its operation. Prior to the fusion procedures, the RPC geolocation parameters of all images are improved in a bundle block adjustment routine. The performance of the algorithm is evaluated on two VHR (Very High Resolution)-satellite image datasets (Pléiades, WorldView-3) revealing its good performance in reconstructing non-textured areas, repetitive patterns, and surface discontinuities.

THE EFFECT OF IMAGE ENHANCEMENT METHODS DURING FEATURE DETECTION AND MATCHING OF THERMAL IMAGES

Directory of Open Access Journals (Sweden)

O. Akcay

2017-05-01

Full Text Available A successful image matching is essential to provide an automatic photogrammetric process accurately. Feature detection, extraction and matching algorithms have performed on the high resolution images perfectly. However, images of cameras, which are equipped with low-resolution thermal sensors are problematic with the current algorithms. In this paper, some digital image processing techniques were applied to the low-resolution images taken with Optris PI 450 382 x 288 pixel optical resolution lightweight thermal camera to increase extraction and matching performance. Image enhancement methods that adjust low quality digital thermal images, were used to produce more suitable images for detection and extraction. Three main digital image process techniques: histogram equalization, high pass and low pass filters were considered to increase the signal-to-noise ratio, sharpen image, remove noise, respectively. Later on, the pre-processed images were evaluated using current image detection and feature extraction methods Maximally Stable Extremal Regions (MSER and Speeded Up Robust Features (SURF algorithms. Obtained results showed that some enhancement methods increased number of extracted features and decreased blunder errors during image matching. Consequently, the effects of different pre-process techniques were compared in the paper.

Optimizing the Attitude Control of Small Satellite Constellations for Rapid Response Imaging

Science.gov (United States)

Nag, S.; Li, A.

2016-12-01

Distributed Space Missions (DSMs) such as formation flight and constellations, are being recognized as important solutions to increase measurement samples over space and time. Given the increasingly accurate attitude control systems emerging in the commercial market, small spacecraft now have the ability to slew and point within few minutes of notice. In spite of hardware development in CubeSats at the payload (e.g. NASA InVEST) and subsystems (e.g. Blue Canyon Technologies), software development for tradespace analysis in constellation design (e.g. Goddard's TAT-C), planning and scheduling development in single spacecraft (e.g. GEO-CAPE) and aerial flight path optimizations for UAVs (e.g. NASA Sensor Web), there is a gap in open-source, open-access software tools for planning and scheduling distributed satellite operations in terms of pointing and observing targets. This paper will demonstrate results from a tool being developed for scheduling pointing operations of narrow field-of-view (FOV) sensors over mission lifetime to maximize metrics such as global coverage and revisit statistics. Past research has shown the need for at least fourteen satellites to cover the Earth globally everyday using a LandSat-like sensor. Increasing the FOV three times reduces the need to four satellites, however adds image distortion and BRDF complexities to the observed reflectance. If narrow FOV sensors on a small satellite constellation were commanded using robust algorithms to slew their sensor dynamically, they would be able to coordinately cover the global landmass much faster without compensating for spatial resolution or BRDF effects. Our algorithm to optimize constellation satellite pointing is based on a dynamic programming approach under the constraints of orbital mechanics and existing attitude control systems for small satellites. As a case study for our algorithm, we minimize the time required to cover the 17000 Landsat images with maximum signal to noise ratio fall

Lineament systems indentification in Banten site using Spot 5 satellite image

International Nuclear Information System (INIS)

Yuliastuti; Heni Susiati; Yunus Daud; A-Sarwiyana Sastratenaya

2013-01-01

Lineament systems identification in Banten site using SPOT 5 satellite image has been performed. Based on regional site survey in Java Island, Banten is one of the potential candidate sites. The objective of this study was to determine direction and chronology of regional lineament morphology which was consider as fault or faulting in Banten site. The methodology used this study covered satellite image cropping, band selection, edge enhancement filtering, lineament extraction and lineament analysis. Result of the study showed that there were three dominant lineament groups, namely N-S, NW-SE, and E-W. Based on the forming chronology of the lineament, N-S group was the oldest one, followed by E-W group and NW-SE as the youngest group. These lineament groups have been confirmed as a manifestation of fault system structure. (author)

PHOTOGRAMMETRIC 3D BUILDING RECONSTRUCTION FROM THERMAL IMAGES

Directory of Open Access Journals (Sweden)

E. Maset

2017-08-01

Full Text Available This paper addresses the problem of 3D building reconstruction from thermal infrared (TIR images. We show that a commercial Computer Vision software can be used to automatically orient sequences of TIR images taken from an Unmanned Aerial Vehicle (UAV and to generate 3D point clouds, without requiring any GNSS/INS data about position and attitude of the images nor camera calibration parameters. Moreover, we propose a procedure based on Iterative Closest Point (ICP algorithm to create a model that combines high resolution and geometric accuracy of RGB images with the thermal information deriving from TIR images. The process can be carried out entirely by the aforesaid software in a simple and efficient way.

Exploiting Deep Matching and SAR Data for the Geo-Localization Accuracy Improvement of Optical Satellite Images

Directory of Open Access Journals (Sweden)

Nina Merkle

2017-06-01

Full Text Available Improving the geo-localization of optical satellite images is an important pre-processing step for many remote sensing tasks like monitoring by image time series or scene analysis after sudden events. These tasks require geo-referenced and precisely co-registered multi-sensor data. Images captured by the high resolution synthetic aperture radar (SAR satellite TerraSAR-X exhibit an absolute geo-location accuracy within a few decimeters. These images represent therefore a reliable source to improve the geo-location accuracy of optical images, which is in the order of tens of meters. In this paper, a deep learning-based approach for the geo-localization accuracy improvement of optical satellite images through SAR reference data is investigated. Image registration between SAR and optical images requires few, but accurate and reliable matching points. These are derived from a Siamese neural network. The network is trained using TerraSAR-X and PRISM image pairs covering greater urban areas spread over Europe, in order to learn the two-dimensional spatial shifts between optical and SAR image patches. Results confirm that accurate and reliable matching points can be generated with higher matching accuracy and precision with respect to state-of-the-art approaches.

Thermally-Induced Chemistry and the Jovian Icy Satellites: A Laboratory Study of the Formation of Sulfur Oxyanions

Science.gov (United States)

Loeffler, Mark J.; Hudson, Reggie L.

2011-01-01

Laboratory experiments have demonstrated that magnetospheric radiation in the Jovian system drives reaction chemistry in ices at temperatures relevant to Europa and other icy satellites. Here we present new results on thermally-induced reactions at 50-100 K in solid H2O-SO2 mixtures, reactions that take place without the need for a high-radiation environment. We find that H2O and SO2 react to produce sulfur Oxyanions, such as bisulfite, that as much as 30% of the SO2 can be consumed through this reaction, and that the products remain in the ice when the temperature is lowered, indicating that these reactions are irreversible. Our results suggest that thermally-induced reactions can alter the chemistry at temperatures relevant to the icy satellites in the Jovian system.

3D modeling of satellite spectral images, radiation budget and energy budget of urban landscapes

Science.gov (United States)

Gastellu-Etchegorry, J. P.

2008-12-01

DART EB is a model that is being developed for simulating the 3D (3 dimensional) energy budget of urban and natural scenes, possibly with topography and atmosphere. It simulates all non radiative energy mechanisms (heat conduction, turbulent momentum and heat fluxes, water reservoir evolution, etc.). It uses DART model (Discrete Anisotropic Radiative Transfer) for simulating radiative mechanisms: 3D radiative budget of 3D scenes and their remote sensing images expressed in terms of reflectance or brightness temperature values, for any atmosphere, wavelength, sun/view direction, altitude and spatial resolution. It uses an innovative multispectral approach (ray tracing, exact kernel, discrete ordinate techniques) over the whole optical domain. This paper presents two major and recent improvements of DART for adapting it to urban canopies. (1) Simulation of the geometry and optical characteristics of urban elements (houses, etc.). (2) Modeling of thermal infrared emission by vegetation and urban elements. The new DART version was used in the context of the CAPITOUL project. For that, districts of the Toulouse urban data base (Autocad format) were translated into DART scenes. This allowed us to simulate visible, near infrared and thermal infrared satellite images of Toulouse districts. Moreover, the 3D radiation budget was used by DARTEB for simulating the time evolution of a number of geophysical quantities of various surface elements (roads, walls, roofs). Results were successfully compared with ground measurements of the CAPITOUL project.

Thermal error analysis and compensation for digital image/volume correlation

Science.gov (United States)

Pan, Bing

2018-02-01

Digital image/volume correlation (DIC/DVC) rely on the digital images acquired by digital cameras and x-ray CT scanners to extract the motion and deformation of test samples. Regrettably, these imaging devices are unstable optical systems, whose imaging geometry may undergo unavoidable slight and continual changes due to self-heating effect or ambient temperature variations. Changes in imaging geometry lead to both shift and expansion in the recorded 2D or 3D images, and finally manifest as systematic displacement and strain errors in DIC/DVC measurements. Since measurement accuracy is always the most important requirement in various experimental mechanics applications, these thermal-induced errors (referred to as thermal errors) should be given serious consideration in order to achieve high accuracy, reproducible DIC/DVC measurements. In this work, theoretical analyses are first given to understand the origin of thermal errors. Then real experiments are conducted to quantify thermal errors. Three solutions are suggested to mitigate or correct thermal errors. Among these solutions, a reference sample compensation approach is highly recommended because of its easy implementation, high accuracy and in-situ error correction capability. Most of the work has appeared in our previously published papers, thus its originality is not claimed. Instead, this paper aims to give a comprehensive overview and more insights of our work on thermal error analysis and compensation for DIC/DVC measurements.

Solar resources estimation combining digital terrain models and satellite images techniques

Energy Technology Data Exchange (ETDEWEB)

Bosch, J.L.; Batlles, F.J. [Universidad de Almeria, Departamento de Fisica Aplicada, Ctra. Sacramento s/n, 04120-Almeria (Spain); Zarzalejo, L.F. [CIEMAT, Departamento de Energia, Madrid (Spain); Lopez, G. [EPS-Universidad de Huelva, Departamento de Ingenieria Electrica y Termica, Huelva (Spain)

2010-12-15

One of the most important steps to make use of any renewable energy is to perform an accurate estimation of the resource that has to be exploited. In the designing process of both active and passive solar energy systems, radiation data is required for the site, with proper spatial resolution. Generally, a radiometric stations network is used in this evaluation, but when they are too dispersed or not available for the study area, satellite images can be utilized as indirect solar radiation measurements. Although satellite images cover wide areas with a good acquisition frequency they usually have a poor spatial resolution limited by the size of the image pixel, and irradiation must be interpolated to evaluate solar irradiation at a sub-pixel scale. When pixels are located in flat and homogeneous areas, correlation of solar irradiation is relatively high, and classic interpolation can provide a good estimation. However, in complex topography zones, data interpolation is not adequate and the use of Digital Terrain Model (DTM) information can be helpful. In this work, daily solar irradiation is estimated for a wide mountainous area using a combination of Meteosat satellite images and a DTM, with the advantage of avoiding the necessity of ground measurements. This methodology utilizes a modified Heliosat-2 model, and applies for all sky conditions; it also introduces a horizon calculation of the DTM points and accounts for the effect of snow covers. Model performance has been evaluated against data measured in 12 radiometric stations, with results in terms of the Root Mean Square Error (RMSE) of 10%, and a Mean Bias Error (MBE) of +2%, both expressed as a percentage of the mean value measured. (author)

AUTOMATIC APPROACH TO VHR SATELLITE IMAGE CLASSIFICATION

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P. Kupidura

2016-06-01

Full Text Available In this paper, we present a proposition of a fully automatic classification of VHR satellite images. Unlike the most widespread approaches: supervised classification, which requires prior defining of class signatures, or unsupervised classification, which must be followed by an interpretation of its results, the proposed method requires no human intervention except for the setting of the initial parameters. The presented approach bases on both spectral and textural analysis of the image and consists of 3 steps. The first step, the analysis of spectral data, relies on NDVI values. Its purpose is to distinguish between basic classes, such as water, vegetation and non-vegetation, which all differ significantly spectrally, thus they can be easily extracted basing on spectral analysis. The second step relies on granulometric maps. These are the product of local granulometric analysis of an image and present information on the texture of each pixel neighbourhood, depending on the texture grain. The purpose of texture analysis is to distinguish between different classes, spectrally similar, but yet of different texture, e.g. bare soil from a built-up area, or low vegetation from a wooded area. Due to the use of granulometric analysis, based on mathematical morphology opening and closing, the results are resistant to the border effect (qualifying borders of objects in an image as spaces of high texture, which affect other methods of texture analysis like GLCM statistics or fractal analysis. Therefore, the effectiveness of the analysis is relatively high. Several indices based on values of different granulometric maps have been developed to simplify the extraction of classes of different texture. The third and final step of the process relies on a vegetation index, based on near infrared and blue bands. Its purpose is to correct partially misclassified pixels. All the indices used in the classification model developed relate to reflectance values, so the

Ground-based thermal imaging of stream surface temperatures: Technique and evaluation

Science.gov (United States)

Bonar, Scott A.; Petre, Sally J.

2015-01-01

We evaluated a ground-based handheld thermal imaging system for measuring water temperatures using data from eight southwestern USA streams and rivers. We found handheld thermal imagers could provide considerably more spatial information on water temperature (for our unit one image = 19,600 individual temperature measurements) than traditional methods could supply without a prohibitive amount of effort. Furthermore, they could provide measurements of stream surface temperature almost instantaneously compared with most traditional handheld thermometers (e.g., >20 s/reading). Spatial temperature analysis is important for measurement of subtle temperature differences across waterways, and identification of warm and cold groundwater inputs. Handheld thermal imaging is less expensive and equipment intensive than airborne thermal imaging methods and is useful under riparian canopies. Disadvantages of handheld thermal imagers include their current higher expense than thermometers, their susceptibility to interference when used incorrectly, and their slightly lower accuracy than traditional temperature measurement methods. Thermal imagers can only measure surface temperature, but this usually corresponds to subsurface temperatures in well-mixed streams and rivers. Using thermal imaging in select applications, such as where spatial investigations of water temperature are needed, or in conjunction with stationary temperature data loggers or handheld electronic or liquid-in-glass thermometers to characterize stream temperatures by both time and space, could provide valuable information on stream temperature dynamics. These tools will become increasingly important to fisheries biologists as costs continue to decline.

NEAR REAL-TIME AUTOMATIC MARINE VESSEL DETECTION ON OPTICAL SATELLITE IMAGES

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G. Máttyus

2013-05-01

Full Text Available Vessel monitoring and surveillance is important for maritime safety and security, environment protection and border control. Ship monitoring systems based on Synthetic-aperture Radar (SAR satellite images are operational. On SAR images the ships made of metal with sharp edges appear as bright dots and edges, therefore they can be well distinguished from the water. Since the radar is independent from the sun light and can acquire images also by cloudy weather and rain, it provides a reliable service. Vessel detection from spaceborne optical images (VDSOI can extend the SAR based systems by providing more frequent revisit times and overcoming some drawbacks of the SAR images (e.g. lower spatial resolution, difficult human interpretation. Optical satellite images (OSI can have a higher spatial resolution thus enabling the detection of smaller vessels and enhancing the vessel type classification. The human interpretation of an optical image is also easier than as of SAR image. In this paper I present a rapid automatic vessel detection method which uses pattern recognition methods, originally developed in the computer vision field. In the first step I train a binary classifier from image samples of vessels and background. The classifier uses simple features which can be calculated very fast. For the detection the classifier is slided along the image in various directions and scales. The detector has a cascade structure which rejects most of the background in the early stages which leads to faster execution. The detections are grouped together to avoid multiple detections. Finally the position, size(i.e. length and width and heading of the vessels is extracted from the contours of the vessel. The presented method is parallelized, thus it runs fast (in minutes for 16000 × 16000 pixels image on a multicore computer, enabling near real-time applications, e.g. one hour from image acquisition to end user.

Near Real-Time Automatic Marine Vessel Detection on Optical Satellite Images

Science.gov (United States)

Máttyus, G.

2013-05-01

Vessel monitoring and surveillance is important for maritime safety and security, environment protection and border control. Ship monitoring systems based on Synthetic-aperture Radar (SAR) satellite images are operational. On SAR images the ships made of metal with sharp edges appear as bright dots and edges, therefore they can be well distinguished from the water. Since the radar is independent from the sun light and can acquire images also by cloudy weather and rain, it provides a reliable service. Vessel detection from spaceborne optical images (VDSOI) can extend the SAR based systems by providing more frequent revisit times and overcoming some drawbacks of the SAR images (e.g. lower spatial resolution, difficult human interpretation). Optical satellite images (OSI) can have a higher spatial resolution thus enabling the detection of smaller vessels and enhancing the vessel type classification. The human interpretation of an optical image is also easier than as of SAR image. In this paper I present a rapid automatic vessel detection method which uses pattern recognition methods, originally developed in the computer vision field. In the first step I train a binary classifier from image samples of vessels and background. The classifier uses simple features which can be calculated very fast. For the detection the classifier is slided along the image in various directions and scales. The detector has a cascade structure which rejects most of the background in the early stages which leads to faster execution. The detections are grouped together to avoid multiple detections. Finally the position, size(i.e. length and width) and heading of the vessels is extracted from the contours of the vessel. The presented method is parallelized, thus it runs fast (in minutes for 16000 × 16000 pixels image) on a multicore computer, enabling near real-time applications, e.g. one hour from image acquisition to end user.

Some selected quantitative methods of thermal image analysis in Matlab.

Science.gov (United States)

Koprowski, Robert

2016-05-01

The paper presents a new algorithm based on some selected automatic quantitative methods for analysing thermal images. It shows the practical implementation of these image analysis methods in Matlab. It enables to perform fully automated and reproducible measurements of selected parameters in thermal images. The paper also shows two examples of the use of the proposed image analysis methods for the area of ​​the skin of a human foot and face. The full source code of the developed application is also provided as an attachment. The main window of the program during dynamic analysis of the foot thermal image. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

THE ANALYSIS OF MOISTURE DEFICIT BASED ON MODIS AND LANDSAT SATELLITE IMAGES. CASE STUDY: THE OLTENIA PLAIN

Directory of Open Access Journals (Sweden)

ONȚEL IRINA

2014-03-01

Full Text Available Satellite images are an important source of information to identify and analyse some hazardous climatic phenomena such as the dryness and drought. These phenomena are characterized by scarce rainfall, increased evapotranspiration and high soil moisture deficit. The soil water reserve depletes to the wilting coefficient, soon followed by the pedological drought which has negative effects on vegetation and agricultural productivity. The MODIS satellite images (Moderate Resolution Imaging Spectroradiometer allow the monitoring of the vegetation throughout the entire vegetative period, with a frequency of 1-2 days and with a spatial resolution of 250 m, 500 m and 1 km away. Another useful source of information is the LANDSAT satellite images, with a spatial resolution of 30 m. Based on MODIS and Landsat satellite images, were calculated moisture monitoring index such as SIWSI (Shortwave Infrared Water Stress Index. Consequently, some years with low moisture such as 2000, 2002, 2007 and 2012 could be identified. Spatially, the areas with moisture deficit varied from one year to another all over the whole analised period (2000-2012. The remote sensing results was corelated with Standard Precipitation Anomaly, which gives a measure of the severity of a wet or dry event.

Urban area thermal monitoring: Liepaja case study using satellite and aerial thermal data

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Gulbe, Linda; Caune, Vairis; Korats, Gundars

2017-12-01

The aim of this study is to explore large (60 m/pixel) and small scale (individual building level) temperature distribution patterns from thermal remote sensing data and to conclude what kind of information could be extracted from thermal remote sensing on regular basis. Landsat program provides frequent large scale thermal images useful for analysis of city temperature patterns. During the study correlation between temperature patterns and vegetation content based on NDVI and building coverage based on OpenStreetMap data was studied. Landsat based temperature patterns were independent from the season, negatively correlated with vegetation content and positively correlated with building coverage. Small scale analysis included spatial and raster descriptor analysis for polygons corresponding to roofs of individual buildings for evaluating insulation of roofs. Remote sensing and spatial descriptors are poorly related to heat consumption data, however, thermal aerial data median and entropy can help to identify poorly insulated roofs. Automated quantitative roof analysis has high potential for acquiring city wide information about roof insulation, but quality is limited by reference data quality and information on building types, and roof materials would be crucial for further studies.

Simultaneous hierarchical segmentation and vectorization of satellite images through combined data sampling and anisotropic triangulation

Energy Technology Data Exchange (ETDEWEB)

Grazzini, Jacopo [Los Alamos National Laboratory; Prasad, Lakshman [Los Alamos National Laboratory; Dillard, Scott [PNNL

2010-10-21

The automatic detection, recognition , and segmentation of object classes in remote sensed images is of crucial importance for scene interpretation and understanding. However, it is a difficult task because of the high variability of satellite data. Indeed, the observed scenes usually exhibit a high degree of complexity, where complexity refers to the large variety of pictorial representations of objects with the same semantic meaning and also to the extensive amount of available det.ails. Therefore, there is still a strong demand for robust techniques for automatic information extraction and interpretation of satellite images. In parallel, there is a growing interest in techniques that can extract vector features directly from such imagery. In this paper, we investigate the problem of automatic hierarchical segmentation and vectorization of multispectral satellite images. We propose a new algorithm composed of the following steps: (i) a non-uniform sampling scheme extracting most salient pixels in the image, (ii) an anisotropic triangulation constrained by the sampled pixels taking into account both strength and directionality of local structures present in the image, (iii) a polygonal grouping scheme merging, through techniques based on perceptual information , the obtained segments to a smaller quantity of superior vectorial objects. Besides its computational efficiency, this approach provides a meaningful polygonal representation for subsequent image analysis and/or interpretation.

The effects of rectification and Global Positioning System errors on satellite image-based estimates of forest area

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Ronald E. McRoberts

2010-01-01

Satellite image-based maps of forest attributes are of considerable interest and are used for multiple purposes such as international reporting by countries that have no national forest inventory and small area estimation for all countries. Construction of the maps typically entails, in part, rectifying the satellite images to a geographic coordinate system, observing...

Accuracy comparison of Pléiades satellite ortho-images using GPS ...

African Journals Online (AJOL)

resolution satellite ortho-image when different types of ground control are used. This required the execution of two orthorectification tests where only the type of GCPs differed. The results of these tests were interesting since it highlighted the ...

Satellite-based ET estimation using Landsat 8 images and SEBAL model

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Bruno Bonemberger da Silva

Full Text Available ABSTRACT Estimation of evapotranspiration is a key factor to achieve sustainable water management in irrigated agriculture because it represents water use of crops. Satellite-based estimations provide advantages compared to direct methods as lysimeters especially when the objective is to calculate evapotranspiration at a regional scale. The present study aimed to estimate the actual evapotranspiration (ET at a regional scale, using Landsat 8 - OLI/TIRS images and complementary data collected from a weather station. SEBAL model was used in South-West Paraná, region composed of irrigated and dry agricultural areas, native vegetation and urban areas. Five Landsat 8 images, row 223 and path 78, DOY 336/2013, 19/2014, 35/2014, 131/2014 and 195/2014 were used, from which ET at daily scale was estimated as a residual of the surface energy balance to produce ET maps. The steps for obtain ET using SEBAL include radiometric calibration, calculation of the reflectance, surface albedo, vegetation indexes (NDVI, SAVI and LAI and emissivity. These parameters were obtained based on the reflective bands of the orbital sensor with temperature surface estimated from thermal band. The estimated ET values in agricultural areas, native vegetation and urban areas using SEBAL algorithm were compatible with those shown in the literature and ET errors between the ET estimates from SEBAL model and Penman Monteith FAO 56 equation were less than or equal to 1.00 mm day-1.

Research on active imaging information transmission technology of satellite borne quantum remote sensing

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Bi, Siwen; Zhen, Ming; Yang, Song; Lin, Xuling; Wu, Zhiqiang

2017-08-01

According to the development and application needs of Remote Sensing Science and technology, Prof. Siwen Bi proposed quantum remote sensing. Firstly, the paper gives a brief introduction of the background of quantum remote sensing, the research status and related researches at home and abroad on the theory, information mechanism and imaging experiments of quantum remote sensing and the production of principle prototype.Then, the quantization of pure remote sensing radiation field, the state function and squeezing effect of quantum remote sensing radiation field are emphasized. It also describes the squeezing optical operator of quantum light field in active imaging information transmission experiment and imaging experiments, achieving 2-3 times higher resolution than that of coherent light detection imaging and completing the production of quantum remote sensing imaging prototype. The application of quantum remote sensing technology can significantly improve both the signal-to-noise ratio of information transmission imaging and the spatial resolution of quantum remote sensing .On the above basis, Prof.Bi proposed the technical solution of active imaging information transmission technology of satellite borne quantum remote sensing, launched researches on its system composition and operation principle and on quantum noiseless amplifying devices, providing solutions and technical basis for implementing active imaging information technology of satellite borne Quantum Remote Sensing.

A fast and automatic mosaic method for high-resolution satellite images

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Chen, Hongshun; He, Hui; Xiao, Hongyu; Huang, Jing

2015-12-01

We proposed a fast and fully automatic mosaic method for high-resolution satellite images. First, the overlapped rectangle is computed according to geographical locations of the reference and mosaic images and feature points on both the reference and mosaic images are extracted by a scale-invariant feature transform (SIFT) algorithm only from the overlapped region. Then, the RANSAC method is used to match feature points of both images. Finally, the two images are fused into a seamlessly panoramic image by the simple linear weighted fusion method or other method. The proposed method is implemented in C++ language based on OpenCV and GDAL, and tested by Worldview-2 multispectral images with a spatial resolution of 2 meters. Results show that the proposed method can detect feature points efficiently and mosaic images automatically.

Satellite imagery in safeguards: progress and prospects

International Nuclear Information System (INIS)

Niemeyer, I.; Listner, C.

2013-01-01

The use of satellite imagery has become very important for the verification of the safeguards implementation under the Nuclear Non-Proliferation Treaty (NPT). The main applications of satellite imagery are to verify the correctness and completeness of the member states' declarations, and to provide preparatory information for inspections, complimentary access and other technical visits. If the area of interest is not accessible, remote sensing sensors provide one of the few opportunities of gathering data for nuclear monitoring, as for example in Iraq between 1998 and 2002 or currently in North Korea. Satellite data of all available sensor types contains a considerable amount of safeguard-relevant information. Very high-resolution optical satellite imagery provides the most detailed spatial information on nuclear sites and activities up to 0.41 m resolution, together with up to 8 spectral bands from the visible light and near infrared. Thermal infrared (TIR) images can indicate the operational status of nuclear facilities and help to identify undeclared activities. Hyper-spectral imagery allows a quantitative estimation of geophysical, geochemical and biochemical characteristics of the earth's surface and is therefore useful for assessing, for example, surface cover changes due to drilling, mining and milling activities. Synthetic Aperture Radar (SAR) image data up to 1 m spatial resolution provides an all-weather, day and night monitoring capability. However, the absence (or existence) of nuclear activities can never be confirmed completely based on satellite imagery. (A.C.)

Automated Detection of Buildings from Heterogeneous VHR Satellite Images for Rapid Response to Natural Disasters

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Shaodan Li

2017-11-01

Full Text Available In this paper, we present a novel approach for automatically detecting buildings from multiple heterogeneous and uncalibrated very high-resolution (VHR satellite images for a rapid response to natural disasters. In the proposed method, a simple and efficient visual attention method is first used to extract built-up area candidates (BACs from each multispectral (MS satellite image. After this, morphological building indices (MBIs are extracted from all the masked panchromatic (PAN and MS images with BACs to characterize the structural features of buildings. Finally, buildings are automatically detected in a hierarchical probabilistic model by fusing the MBI and masked PAN images. The experimental results show that the proposed method is comparable to supervised classification methods in terms of recall, precision and F-value.

Security surveillance challenges and proven thermal imaging capabilities in real-world applications

Science.gov (United States)

Francisco, Glen L.; Roberts, Sharon

2004-09-01

Uncooled thermal imaging was first introduced to the public in early 1980's by Raytheon (legacy Texas Instruments Defense Segment Electronics Group) as a solution for military applications. Since the introduction of this technology, Raytheon has remained the leader in this market as well as introduced commercial versions of thermal imaging products specifically designed for security, law enforcement, fire fighting, automotive and industrial uses. Today, low cost thermal imaging for commercial use in security applications is a reality. Organizations of all types have begun to understand the advantages of using thermal imaging as a means to solve common surveillance problems where other popular technologies fall short. Thermal imaging has proven to be a successful solution for common security needs such as: ¸ vision at night where lighting is undesired and 24x7 surveillance is needed ¸ surveillance over waterways, lakes and ports where water and lighting options are impractical ¸ surveillance through challenging weather conditions where other technologies will be challenged by atmospheric particulates ¸ low maintenance requirements due to remote or difficult locations ¸ low cost over life of product Thermal imaging is now a common addition to the integrated security package. Companies are relying on thermal imaging for specific applications where no other technology can perform.

Use of high resolution satellite images for monitoring of earthquakes and volcano activity.

Science.gov (United States)

Arellano-Baeza, Alonso A.

Our studies have shown that the strain energy accumulation deep in the Earth's crust that precedes a strong earthquake can be detected by applying a lineament extraction technique to the high-resolution multispectral satellite images. A lineament is a straight or a somewhat curved feature in a satellite image, which it is possible to detect by a special processing of images based on directional filtering and or Hough transform. We analyzed tens of earthquakes occurred in the Pacific coast of the South America with the Richter scale magnitude ˜4.5, using ASTER/TERRA multispectral satellite images for detection and analysis of changes in the system of lineaments previous to a strong earthquake. All events were located in the regions with small seasonal variations and limited vegetation to facilitate the tracking of features associated with the seismic activity only. It was found that the number and orientation of lineaments changed significantly about one month before an earthquake approximately, and a few months later the system returns to its initial state. This effect increases with the earthquake magnitude. It also was shown that the behavior of lineaments associated to the volcano seismic activity is opposite to that obtained previously for earthquakes. This discrepancy can be explained assuming that in the last case the main reason of earthquakes is compression and accumulation of strength in the Earth's crust due to subduction of tectonic plates, whereas in the first case we deal with the inflation of a volcano edifice due to elevation of pressure and magma intrusion. The results obtained made it possible to include this research as a part of scientific program of Chilean Remote Sensing Satellite mission to be launched in 2010.

Chagas disease study using satellite image processing: A Bolivian case

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Vargas-Cuentas, Natalia I.; Roman-Gonzalez, Avid; Mantari, Alicia Alva; Muñoz, Luis AnthonyAucapuma

2018-03-01

Remote sensing is the technology that has enabled us to obtain information about the Earth's surface without directly contacting it. For this reason, currently, the Bolivian state has considered a list of interesting applications of remote sensing in the country, including the following: biodiversity and environment monitoring, mining and geology, epidemiology, agriculture, water resources and land use planning. The use of satellite images has become a great tool for epidemiology because with this technological advance we can determine the environment in which transmission occurs, the distribution of the disease and its evolution over time. In that context, one of the important diseases related to public health in Bolivia is Chagas disease, also known as South American Trypanosomiasis. Chagas is caused by a blood-sucking bug or Vinchuca, which causes serious intestinal and heart long term problems and affects 33.4% of the Bolivian population. This disease affects mostly humble people, so the Bolivian state invests millions of dollars to acquire medicine and distribute it for free. Due to the above reasons, the present research aims to analyze some areas of Bolivia using satellite images for developing an epidemiology study. The primary objective is to understand the environment in which the transmission of the disease happens, and the climatic conditions under which occurs, observe the behavior of the blood-sucking bug, identify in which months occur higher outbreaks, in which months the bug leaves its eggs, and under which weather conditions this happens. All this information would be contrasted with information extracted from the satellite images and data from the Ministry of Health, and the Institute of Meteorology in Bolivia. All this data will allow us to have a more integrated understanding of this disease and promote new possibilities to prevent and control it.

Thermal Conductivity Measurements on Icy Satellite Analogs

Science.gov (United States)

Javeed, Aurya; Barmatz, Martin; Zhong, Fang; Choukroun, Mathieu

2012-01-01

With regard to planetary science, NASA aspires to: "Advance scientific knowledge of the origin and history of the solar system, the potential for life elsewhere, and the hazards and resources present as humans explore space". In pursuit of such an end, the Galileo and Cassini missions garnered spectral data of icy satellite surfaces implicative of the satellites' structure and material composition. The potential for geophysical modeling afforded by this information, coupled with the plausibility of life on icy satellites, has pushed Jupiter's Europa along with Saturn's Enceladus and Titan toward the fore of NASA's planetary focus. Understanding the evolution of, and the present processes at work on, the aforementioned satellites falls squarely in-line with NASA's cited goal.

Thermal neutron imaging in an active interrogation environment

International Nuclear Information System (INIS)

Vanier, P.E.; Forman, L.; Norman, D.R.

2009-01-01

We have developed a thermal-neutron coded-aperture imager that reveals the locations of hydrogenous materials from which thermal neutrons are being emitted. This imaging detector can be combined with an accelerator to form an active interrogation system in which fast neutrons are produced in a heavy metal target by means of excitation by high energy photons. The photo-induced neutrons can be either prompt or delayed, depending on whether neutronemitting fission products are generated. Provided that there are hydrogenous materials close to the target, some of the photo-induced neutrons slow down and emerge from the surface at thermal energies. These neutrons can be used to create images that show the location and shape of the thermalizing materials. Analysis of the temporal response of the neutron flux provides information about delayed neutrons from induced fission if there are fissionable materials in the target. The combination of imaging and time-of-flight discrimination helps to improve the signal-to-background ratio. It is also possible to interrogate the target with neutrons, for example using a D-T generator. In this case, an image can be obtained from hydrogenous material in a target without the presence of heavy metal. In addition, if fissionable material is present in the target, probing with fast neutrons can stimulate delayed neutrons from fission, and the imager can detect and locate the object of interest, using appropriate time gating. Operation of this sensitive detection equipment in the vicinity of an accelerator presents a number of challenges, because the accelerator emits electromagnetic interference as well as stray ionizing radiation, which can mask the signals of interest.

One-Dimensional Convective Thermal Evolution Calculation Using a Modified Mixing Length Theory: Application to Saturnian Icy Satellites

Science.gov (United States)

Kamata, Shunichi

2018-01-01

Solid-state thermal convection plays a major role in the thermal evolution of solid planetary bodies. Solving the equation system for thermal evolution considering convection requires 2-D or 3-D modeling, resulting in large calculation costs. A 1-D calculation scheme based on mixing length theory (MLT) requires a much lower calculation cost and is suitable for parameter studies. A major concern for the MLT scheme is its accuracy due to a lack of detailed comparisons with higher dimensional schemes. In this study, I quantify its accuracy via comparisons of thermal profiles obtained by 1-D MLT and 3-D numerical schemes. To improve the accuracy, I propose a new definition of the mixing length (l), which is a parameter controlling the efficiency of heat transportation due to convection, for a bottom-heated convective layer. Adopting this new definition of l, I investigate the thermal evolution of Saturnian icy satellites, Dione and Enceladus, under a wide variety of parameter conditions. Calculation results indicate that each satellite requires several tens of GW of heat to possess a thick global subsurface ocean suggested from geophysical analyses. Dynamical tides may be able to account for such an amount of heat, though the reference viscosity of Dione's ice and the ammonia content of Dione's ocean need to be very high. Otherwise, a thick global ocean in Dione cannot be maintained, implying that its shell is not in a minimum stress state.

Airborne thermal infrared imaging of the 2004-2005 eruption of Mount St. Helens

Science.gov (United States)

Schneider, D. J.; Vallance, J. W.; Logan, M.; Wessels, R.; Ramsey, M.

2005-12-01

A helicopter-mounted forward-looking infrared imaging radiometer (FLIR) documented the explosive and effusive activity at Mount St. Helens during the 2004-2005 eruption. A gyrostabilzed gimbal controlled by a crew member houses the FLIR radiometer and an optical video camera attached at the lower front of the helicopter. Since October 1, 2004 the system has provided an unprecedented data set of thermal and video dome-growth observations. Flights were conducted as frequently as twice daily during the initial month of the eruption (when changes in the crater and dome occurred rapidly), and have been continued on a tri-weekly basis during the period of sustained dome growth. As with any new technology, the routine use of FLIR images to aid in volcano monitoring has been a learning experience in terms of observation strategy and data interpretation. Some of the unique information that has been derived from these data to date include: 1) Rapid identification of the phreatic nature of the early explosive phase; 2) Observation of faulting and associated heat flow during times of large scale deformation; 3) Venting of hot gas through a short lived crater lake, indicative of a shallow magma source; 4) Increased heat flow of the crater floor prior to the initial dome extrusion; 5) Confirmation of new magma reaching the surface; 6) Identification of the source of active lava extrusion, dome collapse, and block and ash flows. Temperatures vary from ambient, in areas insulated by fault gouge and talus produced during extrusion, to as high as 500-740 degrees C in regions of active extrusion, collapse, and fracturing. This temperature variation needs to be accounted for in the retrieval of eruption parameters using satellite-based techniques as such features are sub-pixel size in satellite images.

The Application of Chinese High-Spatial Remote Sensing Satellite Image in Land Law Enforcement Information Extraction

Science.gov (United States)

Wang, N.; Yang, R.

2018-04-01

Chinese high -resolution (HR) remote sensing satellites have made huge leap in the past decade. Commercial satellite datasets, such as GF-1, GF-2 and ZY-3 images, the panchromatic images (PAN) resolution of them are 2 m, 1 m and 2.1 m and the multispectral images (MS) resolution are 8 m, 4 m, 5.8 m respectively have been emerged in recent years. Chinese HR satellite imagery has been free downloaded for public welfare purposes using. Local government began to employ more professional technician to improve traditional land management technology. This paper focused on analysing the actual requirements of the applications in government land law enforcement in Guangxi Autonomous Region. 66 counties in Guangxi Autonomous Region were selected for illegal land utilization spot extraction with fusion Chinese HR images. The procedure contains: A. Defines illegal land utilization spot type. B. Data collection, GF-1, GF-2, and ZY-3 datasets were acquired in the first half year of 2016 and other auxiliary data were collected in 2015. C. Batch process, HR images were collected for batch preprocessing through ENVI/IDL tool. D. Illegal land utilization spot extraction by visual interpretation. E. Obtaining attribute data with ArcGIS Geoprocessor (GP) model. F. Thematic mapping and surveying. Through analysing 42 counties results, law enforcement officials found 1092 illegal land using spots and 16 suspicious illegal mining spots. The results show that Chinese HR satellite images have great potential for feature information extraction and the processing procedure appears robust.

A debugging method of the Quadrotor UAV based on infrared thermal imaging

Science.gov (United States)

Cui, Guangjie; Hao, Qian; Yang, Jianguo; Chen, Lizhi; Hu, Hongkang; Zhang, Lijun

2018-01-01

High-performance UAV has been popular and in great need in recent years. The paper introduces a new method in debugging Quadrotor UAVs. Based on the infrared thermal technology and heat transfer theory, a UAV is under debugging above a hot-wire grid which is composed of 14 heated nichrome wires. And the air flow propelled by the rotating rotors has an influence on the temperature distribution of the hot-wire grid. An infrared thermal imager below observes the distribution and gets thermal images of the hot-wire grid. With the assistance of mathematic model and some experiments, the paper discusses the relationship between thermal images and the speed of rotors. By means of getting debugged UAVs into test, the standard information and thermal images can be acquired. The paper demonstrates that comparing to the standard thermal images, a UAV being debugging in the same test can draw some critical data directly or after interpolation. The results are shown in the paper and the advantages are discussed.

Thermal radiation analysis for small satellites with single-node model using techniques of equivalent linearization

International Nuclear Information System (INIS)

Anh, N.D.; Hieu, N.N.; Chung, P.N.; Anh, N.T.

2016-01-01

Highlights: • Linearization criteria are presented for a single-node model of satellite thermal. • A nonlinear algebraic system for linearization coefficients is obtained. • The temperature evolutions obtained from different methods are explored. • The temperature mean and amplitudes versus the heat capacity are discussed. • The dual criterion approach yields smaller errors than other approximate methods. - Abstract: In this paper, the method of equivalent linearization is extended to the thermal analysis of satellite using both conventional and dual criteria of linearization. These criteria are applied to a differential nonlinear equation of single-node model of the heat transfer of a small satellite in the Low Earth Orbit. A system of nonlinear algebraic equations for linearization coefficients is obtained in the closed form and then solved by the iteration method. The temperature evolution, average values and amplitudes versus the heat capacity obtained by various approaches including Runge–Kutta algorithm, conventional and dual criteria of equivalent linearization, and Grande's approach are compared together. Numerical results reveal that temperature responses obtained from the method of linearization and Grande's approach are quite close to those obtained from the Runge–Kutta method. The dual criterion yields smaller errors than those of the remaining methods when the nonlinearity of the system increases, namely, when the heat capacity varies in the range [1.0, 3.0] × 10 4  J K −1 .

Estimating top-of-atmosphere thermal infrared radiance using MERRA-2 atmospheric data

Science.gov (United States)

Kleynhans, Tania; Montanaro, Matthew; Gerace, Aaron; Kanan, Christopher

2017-05-01

Thermal infrared satellite images have been widely used in environmental studies. However, satellites have limited temporal resolution, e.g., 16 day Landsat or 1 to 2 day Terra MODIS. This paper investigates the use of the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis data product, produced by NASA's Global Modeling and Assimilation Office (GMAO) to predict global topof-atmosphere (TOA) thermal infrared radiance. The high temporal resolution of the MERRA-2 data product presents opportunities for novel research and applications. Various methods were applied to estimate TOA radiance from MERRA-2 variables namely (1) a parameterized physics based method, (2) Linear regression models and (3) non-linear Support Vector Regression. Model prediction accuracy was evaluated using temporally and spatially coincident Moderate Resolution Imaging Spectroradiometer (MODIS) thermal infrared data as reference data. This research found that Support Vector Regression with a radial basis function kernel produced the lowest error rates. Sources of errors are discussed and defined. Further research is currently being conducted to train deep learning models to predict TOA thermal radiance

A diagnostic approach to obtaining planetary boundary layer winds using satellite-derived thermal data

Science.gov (United States)

Belt, Carol L.; Fuelberg, Henry E.

1984-01-01

The feasibility of using satellite derived thermal data to generate realistic synoptic scale winds within the planetary boundary layer (PBL) is examined. Diagnostic modified Ekman wind equations from the Air Force Global Weather Central (AFGWC) Boundary Layer Model are used to compute winds at seven levels within the PBL transition layer (50 m to 1600 m AGL). Satellite derived winds based on 62 predawn TIROS-N soundings are compared to similarly derived wind fields based on 39 AVE-SESAME II rawinsonde (RAOB) soundings taken 2 h later. Actual wind fields are also used as a basis for comparison. Qualitative and statistical comparisons show that the Ekman winds from both sources are in very close agreement, with an average vector correlation coefficient of 0.815. Best results are obtained at 300 m AGL. Satellite winds tend to be slightly weaker than their RAOB counterparts and exhibit a greater degree of cross-isobaric flow. The modified Ekman winds show a significant improvement over geostrophic values at levels nearest the surface.

Three-dimensional information extraction from GaoFen-1 satellite images for landslide monitoring

Science.gov (United States)

Wang, Shixin; Yang, Baolin; Zhou, Yi; Wang, Futao; Zhang, Rui; Zhao, Qing

2018-05-01

To more efficiently use GaoFen-1 (GF-1) satellite images for landslide emergency monitoring, a Digital Surface Model (DSM) can be generated from GF-1 across-track stereo image pairs to build a terrain dataset. This study proposes a landslide 3D information extraction method based on the terrain changes of slope objects. The slope objects are mergences of segmented image objects which have similar aspects; and the terrain changes are calculated from the post-disaster Digital Elevation Model (DEM) from GF-1 and the pre-disaster DEM from GDEM V2. A high mountain landslide that occurred in Wenchuan County, Sichuan Province is used to conduct a 3D information extraction test. The extracted total area of the landslide is 22.58 ha; the displaced earth volume is 652,100 m3; and the average sliding direction is 263.83°. The accuracies of them are 0.89, 0.87 and 0.95, respectively. Thus, the proposed method expands the application of GF-1 satellite images to the field of landslide emergency monitoring.

Status of thermal imaging technology as applied to conservation-update 1

Energy Technology Data Exchange (ETDEWEB)

Snow, F.J.; Wood, J.T.; Barthle, R.C.

1980-07-01

This document updates the 1978 report on the status of thermal imaging technology as applied to energy conservation in buildings. Thermal imaging technology is discussed in terms of airborne surveys, ground survey programs, and application needs such as standards development and lower cost equipment. Information on the various thermal imaging devices was obtained from manufacturer's standard product literature. Listings are provided of infrared projects of the DOE building diagnostics program, of aerial thermographic firms, and of aerial survey programs. (LCL)

Deep learning for the detection of barchan dunes in satellite images

Science.gov (United States)

Azzaoui, A. M.; Adnani, M.; Elbelrhiti, H.; Chaouki, B. E. K.; Masmoudi, L.

2017-12-01

Barchan dunes are known to be the fastest moving sand dunes in deserts as they form under unidirectional winds and limited sand supply over a firm coherent basement (Elbelrhiti and Hargitai,2015). They were studied in the context of natural hazard monitoring as they could be a threat to human activities and infrastructures. Also, they were studied as a natural phenomenon occurring in other planetary landforms such as Mars or Venus (Bourke et al., 2010). Our region of interest was located in a desert region in the south of Morocco, in a barchan dunes corridor next to the town of Tarfaya. This region which is part of the Sahara desert contained thousands of barchans; which limits the number of dunes that could be studied during field missions. Therefore, we chose to monitor barchan dunes with satellite imagery, which can be seen as a complementary approach to field missions. We collected data from the Sentinel platform (https://scihub.copernicus.eu/dhus/); we used a machine learning method as a basis for the detection of barchan dunes positions in the satellite image. We trained a deep learning model on a mid-sized dataset that contained blocks representing images of barchan dunes, and images of other desert features, that we collected by cropping and annotating the source image. During testing, we browsed the satellite image with a gliding window that evaluated each block, and then produced a probability map. Finally, a threshold on the latter map exposed the location of barchan dunes. We used a subsample of data to train the model and we gradually incremented the size of the training set to get finer results and avoid over fitting. The positions of barchan dunes were successfully detected and deep learning was an effective method for this application. Sentinel-2 images were chosen for their availability and good temporal resolution, which will allow the tracking of barchan dunes in future work. While Sentinel images had sufficient spatial resolution for the

Wind Statistics Offshore based on Satellite Images

DEFF Research Database (Denmark)

Hasager, Charlotte Bay; Mouche, Alexis; Badger, Merete

2009-01-01

-based observations become available. At present preliminary results are obtained using the routine methods. The first step in the process is to retrieve raw SAR data, calibrate the images and use a priori wind direction as input to the geophysical model function. From this process the wind speed maps are produced....... The wind maps are geo-referenced. The second process is the analysis of a series of geo-referenced SAR-based wind maps. Previous research has shown that a relatively large number of images are needed for achieving certain accuracies on mean wind speed, Weibull A and k (scale and shape parameters......Ocean wind maps from satellites are routinely processed both at Risø DTU and CLS based on the European Space Agency Envisat ASAR data. At Risø the a priori wind direction is taken from the atmospheric model NOGAPS (Navel Operational Global Atmospheric Prediction System) provided by the U.S. Navy...

A novel algorithm for thermal image encryption.

Science.gov (United States)

Hussain, Iqtadar; Anees, Amir; Algarni, Abdulmohsen

2018-04-16

Thermal images play a vital character at nuclear plants, Power stations, Forensic labs biological research, and petroleum products extraction. Safety of thermal images is very important. Image data has some unique features such as intensity, contrast, homogeneity, entropy and correlation among pixels that is why somehow image encryption is trickier as compare to other encryptions. With conventional image encryption schemes it is normally hard to handle these features. Therefore, cryptographers have paid attention to some attractive properties of the chaotic maps such as randomness and sensitivity to build up novel cryptosystems. That is why, recently proposed image encryption techniques progressively more depends on the application of chaotic maps. This paper proposed an image encryption algorithm based on Chebyshev chaotic map and S8 Symmetric group of permutation based substitution boxes. Primarily, parameters of chaotic Chebyshev map are chosen as a secret key to mystify the primary image. Then, the plaintext image is encrypted by the method generated from the substitution boxes and Chebyshev map. By this process, we can get a cipher text image that is perfectly twisted and dispersed. The outcomes of renowned experiments, key sensitivity tests and statistical analysis confirm that the proposed algorithm offers a safe and efficient approach for real-time image encryption.

Use of a thermal imager for snow pit temperatures

Directory of Open Access Journals (Sweden)

C. Shea

2012-03-01

Full Text Available Weak snow of interest to avalanche forecasting often forms and changes as thin layers. Thermometers, the current field technology for measuring the temperature gradients across such layers – and for thus estimating the expected vapour flux and future type of crystal metamorphism – are difficult to use at distances shorter than 1 cm. In contrast, a thermal imager can provide thousands of simultaneous temperature measurements across small distances with better accuracy. However, a thermal imager only senses the exposed surface, complicating its methods for access and accuracy of buried temperatures. This paper presents methods for exposing buried layers on pit walls and using a thermal imager to measure temperatures on these walls, correct for lens effects with snow, adjust temperature gradients, adjust time exposed, and calculate temperature gradients over millimetre distances. We find lens error on temperature gradients to be on the order of 0.03 °C between image centre and corners. We find temperature gradient change over time to usually decrease – as expected with atmospheric equalization as a strong effect. Case studies including thermal images and visual macro photographs of crystals, collected during the 2010–2011 winter, demonstrate large temperature differences over millimetre-scale distances that are consistent with observed kinetic metamorphism. Further study is needed to use absolute temperatures independently of supporting gradient data.

Robust reflective ghost imaging against different partially polarized thermal light

Science.gov (United States)

Li, Hong-Guo; Wang, Yan; Zhang, Rui-Xue; Zhang, De-Jian; Liu, Hong-Chao; Li, Zong-Guo; Xiong, Jun

2018-03-01

We theoretically study the influence of degree of polarization (DOP) of thermal light on the contrast-to-noise ratio (CNR) of the reflective ghost imaging (RGI), which is a novel and indirect imaging modality. An expression for the CNR of RGI with partially polarized thermal light is carefully derived, which suggests a weak dependence of CNR on the DOP, especially when the ratio of the object size to the speckle size of thermal light has a large value. Different from conventional imaging approaches, our work reveals that RGI is much more robust against the DOP of the light source, which thereby has advantages in practical applications, such as remote sensing.

Detection of Convective Initiation Using Meteorological Imager Onboard Communication, Ocean, and Meteorological Satellite Based on Machine Learning Approaches

Directory of Open Access Journals (Sweden)

Hyangsun Han

2015-07-01

Full Text Available As convective clouds in Northeast Asia are accompanied by various hazards related with heavy rainfall and thunderstorms, it is very important to detect convective initiation (CI in the region in order to mitigate damage by such hazards. In this study, a novel approach for CI detection using images from Meteorological Imager (MI, a payload of the Communication, Ocean, and Meteorological Satellite (COMS, was developed by improving the criteria of the interest fields of Rapidly Developing Cumulus Areas (RDCA derivation algorithm, an official CI detection algorithm for Multi-functional Transport SATellite-2 (MTSAT-2, based on three machine learning approaches—decision trees (DT, random forest (RF, and support vector machines (SVM. CI was defined as clouds within a 16 × 16 km window with the first detection of lightning occurrence at the center. A total of nine interest fields derived from visible, water vapor, and two thermal infrared images of MI obtained 15–75 min before the lightning occurrence were used as input variables for CI detection. RF produced slightly higher performance (probability of detection (POD of 75.5% and false alarm rate (FAR of 46.2% than DT (POD of 70.7% and FAR of 46.6% for detection of CI caused by migrating frontal cyclones and unstable atmosphere. SVM resulted in relatively poor performance with very high FAR ~83.3%. The averaged lead times of CI detection based on the DT and RF models were 36.8 and 37.7 min, respectively. This implies that CI over Northeast Asia can be forecasted ~30–45 min in advance using COMS MI data.

Use of satellite images for the monitoring of water systems

Science.gov (United States)

Hillebrand, Gudrun; Winterscheid, Axel; Baschek, Björn; Wolf, Thomas

2015-04-01

Satellite images are a proven source of information for monitoring ecological indicators in coastal waters and inland river systems. This potential of remote sensing products was demonstrated by recent research projects (e.g. EU-funded project Freshmon - www.freshmon.eu) and other activities by national institutions. Among indicators for water quality, a particular focus was set on the temporal and spatial dynamics of suspended particulate matter (SPM) and Chlorophyll-a (Chl-a). The German Federal Institute of Hydrology (BfG) was using the Weser and Elbe estuaries as test cases to compare in-situ measurements with results obtained from a temporal series of automatically generated maps of SPM distributions based on remote sensing data. Maps of SPM and Chl-a distributions in European inland rivers and alpine lakes were generated by the Freshmon Project. Earth observation based products are a valuable source for additional data that can well supplement in-situ monitoring. For 2015, the BfG and the Institute for Lake Research of the State Institute for the Environment, Measurements and Nature Conservation of Baden-Wuerttemberg, Germany (LUBW) are in the process to start implementing an operational service for monitoring SPM and Chl-a based on satellite images (Landsat 7 & 8, Sentinel 2, and if required other systems with higher spatial resolution, e.g. Rapid Eye). In this 2-years project, which is part of the European Copernicus Programme, the operational service will be set up for - the inland rivers of Rhine and Elbe - the North Sea estuaries of Elbe, Weser and Ems. Furthermore - Lake Constance and other lakes located within the Federal State of Baden-Wuerttemberg. In future, the service can be implemented for other rivers and lakes as well. Key feature of the project is a data base that holds the stock of geo-referenced maps of SPM and Chl-a distributions. Via web-based portals (e.g. GGInA - geo-portal of the BfG; UIS - environmental information system of the

Reconstructing Face Image from the Thermal Infrared Spectrum to the Visible Spectrum

Directory of Open Access Journals (Sweden)

Brahmastro Kresnaraman

2016-04-01

Full Text Available During the night or in poorly lit areas, thermal cameras are a better choice instead of normal cameras for security surveillance because they do not rely on illumination. A thermal camera is able to detect a person within its view, but identification from only thermal information is not an easy task. The purpose of this paper is to reconstruct the face image of a person from the thermal spectrum to the visible spectrum. After the reconstruction, further image processing can be employed, including identification/recognition. Concretely, we propose a two-step thermal-to-visible-spectrum reconstruction method based on Canonical Correlation Analysis (CCA. The reconstruction is done by utilizing the relationship between images in both thermal infrared and visible spectra obtained by CCA. The whole image is processed in the first step while the second step processes patches in an image. Results show that the proposed method gives satisfying results with the two-step approach and outperforms comparative methods in both quality and recognition evaluations.

The 2017 Hurricane Season: A Revolution in Geostationary Weather Satellite Imaging and Data Processing

Science.gov (United States)

Weiner, A. M.; Gundy, J.; Brown-Bertold, B.; Yates, H.; Dobler, J. T.

2017-12-01

Since their introduction, geostationary weather satellites have enabled us to track hurricane life-cycle movement from development to dissipation. During the 2017 hurricane season, the new GOES-16 geostationary satellite demonstrated just how far we have progressed technologically in geostationary satellite imaging, with hurricane imagery showing never-before-seen detail of the hurricane eye and eyewall structure and life cycle. In addition, new ground system technology, leveraging high-performance computing, delivered imagery and data to forecasters with unprecedented speed—and with updates as often as every 30 seconds. As additional satellites and new products become operational, forecasters will be able to track hurricanes with even greater accuracy and assist in aftermath evaluations. This presentation will present glimpses into the past, a look at the present, and a prediction for the future utilization of geostationary satellites with respect to all facets of hurricane support.

Performance evaluation of a thermal Doppler Michelson interferometer system.

Science.gov (United States)

Mani, Reza; Dobbie, Steven; Scott, Alan; Shepherd, Gordon; Gault, William; Brown, Stephen

2005-11-20

The thermal Doppler Michelson interferometer is the primary element of a proposed limb-viewing satellite instrument called SWIFT (Stratospheric Wind Interferometer for Transport studies). SWIFT is intended to measure stratospheric wind velocities in the altitude range of 15-45 km. SWIFT also uses narrowband tandem etalon filters made of germanium to select a line out of the thermal spectrum. The instrument uses the same technique of phase-stepping interferometry employed by the Wind Imaging Interferometer onboard the Upper Atmosphere Research Satellite. A thermal emission line of ozone near 9 microm is used to detect the Doppler shift due to winds. A test bed was set up for this instrument that included the Michelson interferometer and the etalon filters. For the test bed work, we investigate the behavior of individual components and their combination and report the results.

Quantitative subsurface analysis using frequency modulated thermal wave imaging

Science.gov (United States)

Subhani, S. K.; Suresh, B.; Ghali, V. S.

2018-01-01

Quantitative depth analysis of the anomaly with an enhanced depth resolution is a challenging task towards the estimation of depth of the subsurface anomaly using thermography. Frequency modulated thermal wave imaging introduced earlier provides a complete depth scanning of the object by stimulating it with a suitable band of frequencies and further analyzing the subsequent thermal response using a suitable post processing approach to resolve subsurface details. But conventional Fourier transform based methods used for post processing unscramble the frequencies with a limited frequency resolution and contribute for a finite depth resolution. Spectral zooming provided by chirp z transform facilitates enhanced frequency resolution which can further improves the depth resolution to axially explore finest subsurface features. Quantitative depth analysis with this augmented depth resolution is proposed to provide a closest estimate to the actual depth of subsurface anomaly. This manuscript experimentally validates this enhanced depth resolution using non stationary thermal wave imaging and offers an ever first and unique solution for quantitative depth estimation in frequency modulated thermal wave imaging.

Feature Extraction in Sequential Multimedia Images: with Applications in Satellite Images and On-line Videos

Science.gov (United States)

Liang, Yu-Li

Multimedia data is increasingly important in scientific discovery and people's daily lives. Content of massive multimedia is often diverse and noisy, and motion between frames is sometimes crucial in analyzing those data. Among all, still images and videos are commonly used formats. Images are compact in size but do not contain motion information. Videos record motion but are sometimes too big to be analyzed. Sequential images, which are a set of continuous images with low frame rate, stand out because they are smaller than videos and still maintain motion information. This thesis investigates features in different types of noisy sequential images, and the proposed solutions that intelligently combined multiple features to successfully retrieve visual information from on-line videos and cloudy satellite images. The first task is detecting supraglacial lakes above ice sheet in sequential satellite images. The dynamics of supraglacial lakes on the Greenland ice sheet deeply affect glacier movement, which is directly related to sea level rise and global environment change. Detecting lakes above ice is suffering from diverse image qualities and unexpected clouds. A new method is proposed to efficiently extract prominent lake candidates with irregular shapes, heterogeneous backgrounds, and in cloudy images. The proposed system fully automatize the procedure that track lakes with high accuracy. We further cooperated with geoscientists to examine the tracked lakes and found new scientific findings. The second one is detecting obscene content in on-line video chat services, such as Chatroulette, that randomly match pairs of users in video chat sessions. A big problem encountered in such systems is the presence of flashers and obscene content. Because of various obscene content and unstable qualities of videos capture by home web-camera, detecting misbehaving users is a highly challenging task. We propose SafeVchat, which is the first solution that achieves satisfactory

Using Deep Learning Model for Meteorological Satellite Cloud Image Prediction

Science.gov (United States)

Su, X.

2017-12-01

A satellite cloud image contains much weather information such as precipitation information. Short-time cloud movement forecast is important for precipitation forecast and is the primary means for typhoon monitoring. The traditional methods are mostly using the cloud feature matching and linear extrapolation to predict the cloud movement, which makes that the nonstationary process such as inversion and deformation during the movement of the cloud is basically not considered. It is still a hard task to predict cloud movement timely and correctly. As deep learning model could perform well in learning spatiotemporal features, to meet this challenge, we could regard cloud image prediction as a spatiotemporal sequence forecasting problem and introduce deep learning model to solve this problem. In this research, we use a variant of Gated-Recurrent-Unit(GRU) that has convolutional structures to deal with spatiotemporal features and build an end-to-end model to solve this forecast problem. In this model, both the input and output are spatiotemporal sequences. Compared to Convolutional LSTM(ConvLSTM) model, this model has lower amount of parameters. We imply this model on GOES satellite data and the model perform well.

Thermal Analysis of Iodine Satellite (iSAT) from Preliminary Design Review (PDR) to Critical Design Review (CDR)

Science.gov (United States)

Mauro, Stephanie

2016-01-01

The Iodine Satellite (iSAT) is a 12U cubesat with a primary mission to demonstrate the iodine fueled Hall Effect Thruster (HET) propulsion system. The spacecraft (SC) will operate throughout a one year mission in an effort to mature the propulsion system for use in future applications. The benefit of the HET is that it uses a propellant, iodine, which is easy to store and provides a high thrust-to-mass ratio. This paper will describe the thermal analysis and design of the SC between Preliminary Design Review (PDR) and Critical Design Review (CDR). The design of the satellite has undergone many changes due to a variety of challenges, both before PDR and during the time period discussed in this paper. Thermal challenges associated with the system include a high power density, small amounts of available radiative surface area, localized temperature requirements of the propulsion components, and unknown orbital parameters. The thermal control system is implemented to maintain component temperatures within their respective operational limits throughout the mission, while also maintaining propulsion components at the high temperatures needed to allow gaseous iodine propellant to flow. The design includes heaters, insulation, radiators, coatings, and thermal straps. Currently, the maximum temperatures for several components are near to their maximum operation limit, and the battery is close to its minimum operation limit. Mitigation strategies and planned work to solve these challenges will be discussed.

Thermal Imaging Performance of TIR Onboard the Hayabusa2 Spacecraft

Science.gov (United States)

Arai, Takehiko; Nakamura, Tomoki; Tanaka, Satoshi; Demura, Hirohide; Ogawa, Yoshiko; Sakatani, Naoya; Horikawa, Yamato; Senshu, Hiroki; Fukuhara, Tetsuya; Okada, Tatsuaki

2017-07-01

The thermal infrared imager (TIR) is a thermal infrared camera onboard the Hayabusa2 spacecraft. TIR will perform thermography of a C-type asteroid, 162173 Ryugu (1999 JU3), and estimate its surface physical properties, such as surface thermal emissivity ɛ , surface roughness, and thermal inertia Γ, through remote in-situ observations in 2018 and 2019. In prelaunch tests of TIR, detector calibrations and evaluations, along with imaging demonstrations, were performed. The present paper introduces the experimental results of a prelaunch test conducted using a large-aperture collimator in conjunction with TIR under atmospheric conditions. A blackbody source, controlled at constant temperature, was measured using TIR in order to construct a calibration curve for obtaining temperatures from observed digital data. As a known thermal emissivity target, a sandblasted black almite plate warmed from the back using a flexible heater was measured by TIR in order to evaluate the accuracy of the calibration curve. As an analog target of a C-type asteroid, carbonaceous chondrites (50 mm × 2 mm in thickness) were also warmed from the back and measured using TIR in order to clarify the imaging performance of TIR. The calibration curve, which was fitted by a specific model of the Planck function, allowed for conversion to the target temperature within an error of 1°C (3σ standard deviation) for the temperature range of 30 to 100°C. The observed temperature of the black almite plate was consistent with the temperature measured using K-type thermocouples, within the accuracy of temperature conversion using the calibration curve when the temperature variation exhibited a random error of 0.3 °C (1σ ) for each pixel at a target temperature of 50°C. TIR can resolve the fine surface structure of meteorites, including cracks and pits with the specified field of view of 0.051°C (328 × 248 pixels). There were spatial distributions with a temperature variation of 3°C at the setting

Solar irradiance assessment in insular areas using Himawari-8 satellite images

Science.gov (United States)

Liandrat, O.; Cros, S.; Turpin, M.; Pineau, J. F.

2016-12-01

The high amount of surface solar irradiance (SSI) in the tropics is an advantage for a profitable PV production. It will allow many tropical islands to pursue their economic growth with a clean, affordable and locally produced energy. However, the local meteorological conditions induce a very high variability which is problematic for a safe and gainful injection into the power grid. This issue is even more critical in non-interconnected territories where network stability is an absolute necessity. Therefore, the injection of PV power is legally limited in some European oversea territories. In this context, intraday irradiance forecasting (several hours ahead) is particularly useful to mitigate the production variability by reducing the cost of power storage management. At this time scale, cloud cover evolves with a stochastic behaviour not properly represented in numerical weather prediction (NWP) models. Analysing cloud motion using images from geostationary meteorological satellites is a well-known alternative to forecasting SSI up to 6 hours ahead with a better accuracy than NWP models. In this study, we present and apply our satellite-based solar irradiance forecasting methods over two measurement sites located in the field of view of the satellite Himawari-8: Cocos (Keeling) Islands (Australia) and New Caledonia (France). In particular, we converted 4 months of images from Himawari-8 visible channel into cloud index maps. Then, we applied an algorithm computing a cloud motion vector field from a short sequence of consecutive images. Comparisons between forecasted SSI at 1 hour of time horizon and collocated pyranometric measurements show a relative RMSE between 20 and 27%. Error sources related to the tropic insular context (coastal area heterogeneity, sub-pixel scale orographic cloud appearance, convective situation…) are discussed at every implementation step for the different methods.

Automatic Matching of Multi-Source Satellite Images: A Case Study on ZY-1-02C and ETM+

Directory of Open Access Journals (Sweden)

Bo Wang

2017-10-01

Full Text Available The ever-growing number of applications for satellites is being compromised by their poor direct positioning precision. Existing orthoimages, such as enhanced thematic mapper (ETM+ orthoimages, can provide georeferences or improve the geo-referencing accuracy of satellite images, such ZY-1-02C images that have unsatisfactory positioning precision, thus enhancing their processing efficiency and application. In this paper, a feasible image matching approach using multi-source satellite images is proposed on the basis of an experiment carried out with ZY-1-02C Level 1 images and ETM+ orthoimages. The proposed approach overcame differences in rotation angle, scale, and translation between images. The rotation and scale variances were evaluated on the basis of rational polynomial coefficients. The translation vectors were generated after blocking the overall phase correlation. Then, normalized cross-correlation and least-squares matching were applied for matching. Finally, the gross errors of the corresponding points were eliminated by local statistic vectors in a TIN structure. Experimental results showed a matching precision of less than two pixels (root-mean-square error, and comparison results indicated that the proposed method outperforms Scale-Invariant Feature Transform (SIFT, Speeded Up Robust Features (SURF, and Affine-Scale Invariant Feature Transform (A-SIFT in terms of reliability and efficiency.

An anti-image interference quadrature IF architecture for satellite receivers

Directory of Open Access Journals (Sweden)

He Weidong

2014-08-01

Full Text Available Since Global Navigation Satellite System (GNSS signals span a wide range of frequency, wireless signals coming from other communication systems may be aliased and appear as image interference. In quadrature intermediate frequency (IF receivers, image aliasing due to in-phase and quadrature (I/Q channel mismatches is always a big problem. I/Q mismatches occur because of gain and phase imbalances between quadrature mixers and capacitor mismatches in analog-to-digital converters (ADC. As a result, the dynamic range and performance of a receiver are severely degraded. In this paper, several popular receiver architectures are summarized and the image aliasing problem is investigated in detail. Based on this analysis, a low-IF architecture is proposed for a single-chip solution and a novel and feasible anti-image algorithm is investigated. With this anti-image digital processing, the image reject ratio (IRR can reach approximately above 50 dB, which relaxes image rejection specific in front-end circuit designs and allows cheap and highly flexible analog front-end solutions. Simulation and experimental data show that the anti-image algorithm can work effectively, robustly, and steadily.

Online thermal imaging: a simple approach

Science.gov (United States)

Senior, Mark; Hollock, Steve; Sandhu, Sat; Coy, Joanne; Parkin, Rob

2003-04-01

Continuous monitoring of plant and processes is widely practised but the use of thermal imagers in such systems has always been restricted by camera cost. A radiometric thermal imager can be regarded as equivalent to multiple single point radiometers or a matrix of thermocouples but with the advantages of far denser coverage, non-contact measurement, simpler installation and data processing; in addition several of the advantages of conventional machine vision systems such as shape and position recognition can be provided. IRISYS has developed a multipoint radiometer utilising its low-cost infrared array technology. This unit provides continuous real-time temperature monitoring of 256 data points at an affordable price; it is housed in a small, light-weight, sealed and robust metal case and generates RS232 or Ethernet data output. This paper reviews the radiometer technology and its application to single and multi-camera systems.

Laser Guidestar Satellite for Ground-based Adaptive Optics Imaging of Geosynchronous Satellites and Astronomical Targets

Science.gov (United States)

Marlow, W. A.; Cahoy, K.; Males, J.; Carlton, A.; Yoon, H.

2015-12-01

Real-time observation and monitoring of geostationary (GEO) satellites with ground-based imaging systems would be an attractive alternative to fielding high cost, long lead, space-based imagers, but ground-based observations are inherently limited by atmospheric turbulence. Adaptive optics (AO) systems are used to help ground telescopes achieve diffraction-limited seeing. AO systems have historically relied on the use of bright natural guide stars or laser guide stars projected on a layer of the upper atmosphere by ground laser systems. There are several challenges with this approach such as the sidereal motion of GEO objects relative to natural guide stars and limitations of ground-based laser guide stars; they cannot be used to correct tip-tilt, they are not point sources, and have finite angular sizes when detected at the receiver. There is a difference between the wavefront error measured using the guide star compared with the target due to cone effect, which also makes it difficult to use a distributed aperture system with a larger baseline to improve resolution. Inspired by previous concepts proposed by A.H. Greenaway, we present using a space-based laser guide starprojected from a satellite orbiting the Earth. We show that a nanosatellite-based guide star system meets the needs for imaging GEO objects using a low power laser even from 36,000 km altitude. Satellite guide star (SGS) systemswould be well above atmospheric turbulence and could provide a small angular size reference source. CubeSatsoffer inexpensive, frequent access to space at a fraction of the cost of traditional systems, and are now being deployed to geostationary orbits and on interplanetary trajectories. The fundamental CubeSat bus unit of 10 cm cubed can be combined in multiple units and offers a common form factor allowing for easy integration as secondary payloads on traditional launches and rapid testing of new technologies on-orbit. We describe a 6U CubeSat SGS measuring 10 cm x 20 cm x

Synchronous atmospheric radiation correction of GF-2 satellite multispectral image

Science.gov (United States)

Bian, Fuqiang; Fan, Dongdong; Zhang, Yan; Wang, Dandan

2018-02-01

GF-2 remote sensing products have been widely used in many fields for its high-quality information, which provides technical support for the the macroeconomic decisions. Atmospheric correction is the necessary part in the data preprocessing of the quantitative high resolution remote sensing, which can eliminate the signal interference in the radiation path caused by atmospheric scattering and absorption, and reducting apparent reflectance into real reflectance of the surface targets. Aiming at the problem that current research lack of atmospheric date which are synchronization and region matching of the surface observation image, this research utilize the MODIS Level 1B synchronous data to simulate synchronized atmospheric condition, and write programs to implementation process of aerosol retrieval and atmospheric correction, then generate a lookup table of the remote sensing image based on the radioactive transfer model of 6S (second simulation of a satellite signal in the solar spectrum) to correct the atmospheric effect of multispectral image from GF-2 satellite PMS-1 payload. According to the correction results, this paper analyzes the pixel histogram of the reflectance spectrum of the 4 spectral bands of PMS-1, and evaluates the correction results of different spectral bands. Then conducted a comparison experiment on the same GF-2 image based on the QUAC. According to the different targets respectively statistics the average value of NDVI, implement a comparative study of NDVI from two different results. The degree of influence was discussed by whether to adopt synchronous atmospheric date. The study shows that the result of the synchronous atmospheric parameters have significantly improved the quantitative application of the GF-2 remote sensing data.

Application of optical character recognition in thermal image processing

Science.gov (United States)

Chan, W. T.; Sim, K. S.; Tso, C. P.

2011-07-01

This paper presents the results of a study on the reliability of the thermal imager compared to other devices that are used in preventive maintenance. Several case studies are used to facilitate the comparisons. When any device is found to perform unsatisfactorily where there is a suspected fault, its short-fall is determined so that the other devices may compensate, if possible. This study discovered that the thermal imager is not suitable or efficient enough for systems that happen to have little contrast in temperature between its parts or small but important parts that have their heat signatures obscured by those from other parts. The thermal imager is also found to be useful for preliminary examinations of certain systems, after which other more economical devices are suitable substitutes for further examinations. The findings of this research will be useful to the design and planning of preventive maintenance routines for industrial benefits.

Evaluation of Three Parametric Models for Estimating Directional Thermal Radiation from Simulation, Airborne, and Satellite Data

Directory of Open Access Journals (Sweden)

Xiangyang Liu

2018-03-01

Full Text Available An appropriate model to correct thermal radiation anisotropy is important for the wide applications of land surface temperature (LST. This paper evaluated the performance of three published directional thermal radiation models—the Roujean–Lagouarde (RL model, the Bidirectional Reflectance Distribution Function (BRDF model, and the Vinnikov model—at canopy and pixel scale using simulation, airborne, and satellite data. The results at canopy scale showed that (1 the three models could describe directional anisotropy well and the Vinnikov model performed the best, especially for erectophile canopy or low leaf area index (LAI; (2 the three models reached the highest fitting accuracy when the LAI varied from 1 to 2; and (3 the capabilities of the three models were all restricted by the hotspot effect, plant height, plant spacing, and three-dimensional structure. The analysis at pixel scale indicated a consistent result that the three models presented a stable effect both on verification and validation, but the Vinnikov model had the best ability in the erectophile canopy (savannas and grassland and low LAI (barren or sparsely vegetated areas. Therefore, the Vinnikov model was calibrated for different land cover types to instruct the angular correction of LST. Validation with the Surface Radiation Budget Network (SURFRAD-measured LST demonstrated that the root mean square (RMSE of the Moderate Resolution Imaging Spectroradiometer (MODIS LST product could be decreased by 0.89 K after angular correction. In addition, the corrected LST showed better spatial uniformity and higher angular correlation.

Mapping urban impervious surface using object-based image analysis with WorldView-3 satellite imagery

Science.gov (United States)

Iabchoon, Sanwit; Wongsai, Sangdao; Chankon, Kanoksuk

2017-10-01

Land use and land cover (LULC) data are important to monitor and assess environmental change. LULC classification using satellite images is a method widely used on a global and local scale. Especially, urban areas that have various LULC types are important components of the urban landscape and ecosystem. This study aims to classify urban LULC using WorldView-3 (WV-3) very high-spatial resolution satellite imagery and the object-based image analysis method. A decision rules set was applied to classify the WV-3 images in Kathu subdistrict, Phuket province, Thailand. The main steps were as follows: (1) the image was ortho-rectified with ground control points and using the digital elevation model, (2) multiscale image segmentation was applied to divide the image pixel level into image object level, (3) development of the decision ruleset for LULC classification using spectral bands, spectral indices, spatial and contextual information, and (4) accuracy assessment was computed using testing data, which sampled by statistical random sampling. The results show that seven LULC classes (water, vegetation, open space, road, residential, building, and bare soil) were successfully classified with overall classification accuracy of 94.14% and a kappa coefficient of 92.91%.

Comparison of the signal-to-noise characteristics of quantum versus thermal ghost imaging

International Nuclear Information System (INIS)

O'Sullivan, Malcolm N.; Chan, Kam Wai Clifford; Boyd, Robert W.

2010-01-01

We present a theoretical comparison of the signal-to-noise characteristics of quantum versus thermal ghost imaging. We first calculate the signal-to-noise ratio of each process in terms of its controllable experimental conditions. We show that a key distinction is that a thermal ghost image always resides on top of a large background; the fluctuations in this background constitutes an intrinsic noise source for thermal ghost imaging. In contrast, there is a negligible intrinsic background to a quantum ghost image. However, for practical reasons involving achievable illumination levels, acquisition times for thermal ghost images are often much shorter than those for quantum ghost images. We provide quantitative predictions for the conditions under which each process provides superior performance. Our conclusion is that each process can provide useful functionality, although under complementary conditions.

Band co-registration modeling of LAPAN-A3/IPB multispectral imager based on satellite attitude

Science.gov (United States)

Hakim, P. R.; Syafrudin, A. H.; Utama, S.; Jayani, A. P. S.

2018-05-01

One of significant geometric distortion on images of LAPAN-A3/IPB multispectral imager is co-registration error between each color channel detector. Band co-registration distortion usually can be corrected by using several approaches, which are manual method, image matching algorithm, or sensor modeling and calibration approach. This paper develops another approach to minimize band co-registration distortion on LAPAN-A3/IPB multispectral image by using supervised modeling of image matching with respect to satellite attitude. Modeling results show that band co-registration error in across-track axis is strongly influenced by yaw angle, while error in along-track axis is fairly influenced by both pitch and roll angle. Accuracy of the models obtained is pretty good, which lies between 1-3 pixels error for each axis of each pair of band co-registration. This mean that the model can be used to correct the distorted images without the need of slower image matching algorithm, nor the laborious effort needed in manual approach and sensor calibration. Since the calculation can be executed in order of seconds, this approach can be used in real time quick-look image processing in ground station or even in satellite on-board image processing.

High efficient optical remote sensing images acquisition for nano-satellite: reconstruction algorithms

Science.gov (United States)

Liu, Yang; Li, Feng; Xin, Lei; Fu, Jie; Huang, Puming

2017-10-01

Large amount of data is one of the most obvious features in satellite based remote sensing systems, which is also a burden for data processing and transmission. The theory of compressive sensing(CS) has been proposed for almost a decade, and massive experiments show that CS has favorable performance in data compression and recovery, so we apply CS theory to remote sensing images acquisition. In CS, the construction of classical sensing matrix for all sparse signals has to satisfy the Restricted Isometry Property (RIP) strictly, which limits applying CS in practical in image compression. While for remote sensing images, we know some inherent characteristics such as non-negative, smoothness and etc.. Therefore, the goal of this paper is to present a novel measurement matrix that breaks RIP. The new sensing matrix consists of two parts: the standard Nyquist sampling matrix for thumbnails and the conventional CS sampling matrix. Since most of sun-synchronous based satellites fly around the earth 90 minutes and the revisit cycle is also short, lots of previously captured remote sensing images of the same place are available in advance. This drives us to reconstruct remote sensing images through a deep learning approach with those measurements from the new framework. Therefore, we propose a novel deep convolutional neural network (CNN) architecture which takes in undersampsing measurements as input and outputs an intermediate reconstruction image. It is well known that the training procedure to the network costs long time, luckily, the training step can be done only once, which makes the approach attractive for a host of sparse recovery problems.

A Data Mining Approach for Sharpening Thermal Satellite Imagery over Land

Directory of Open Access Journals (Sweden)

Feng Gao

2012-10-01

Full Text Available Thermal infrared (TIR imagery is normally acquired at coarser pixel resolution than that of shortwave sensors on the same satellite platform and often the TIR resolution is not suitable for monitoring crop conditions of individual fields or the impacts of land cover changes that are at significantly finer spatial scales. Consequently, thermal sharpening techniques have been developed to sharpen TIR imagery to shortwave band pixel resolutions, which are often fine enough for field-scale applications. A classic thermal sharpening technique, TsHARP, uses a relationship between land surface temperature (LST and Normalized Difference Vegetation Index (NDVI developed empirically at the TIR pixel resolution and applied at the NDVI pixel resolution. However, recent studies show that unique relationships between temperature and NDVI may only exist for a limited class of landscapes, with mostly green vegetation and homogeneous air and soil conditions. To extend application of thermal sharpening to more complex conditions, a new data mining sharpener (DMS technique is developed. The DMS approach builds regression trees between TIR band brightness temperatures and shortwave spectral reflectances based on intrinsic sample characteristics. A comparison of sharpening techniques applied over a rainfed agricultural area in central Iowa, an irrigated agricultural region in the Texas High Plains, and a heterogeneous naturally vegetated landscape in Alaska indicates that the DMS outperformed TsHARP in all cases. The artificial box-like patterns in LST generated by the TsHARP approach are greatly reduced using the DMS scheme, especially for areas containing irrigated crops, water bodies, thin clouds or terrain. While the DMS technique can provide fine resolution TIR imagery, there are limits to the sharpening ratios that can be reasonably implemented. Consequently, sharpening techniques cannot replace actual thermal band imagery at fine resolutions or missions that

A Thermal Imaging Instrument with Uncooled Detectors

Data.gov (United States)

National Aeronautics and Space Administration — In this proposed work, we will perform an instrument concept study for sustainable thermal imaging over land with uncooled detectors. We will define the science and...

DETECTION OF BARCHAN DUNES IN HIGH RESOLUTION SATELLITE IMAGES

Directory of Open Access Journals (Sweden)

M. A. Azzaoui

2016-06-01

Full Text Available Barchan dunes are the fastest moving sand dunes in the desert. We developed a process to detect barchans dunes on High resolution satellite images. It consisted of three steps, we first enhanced the image using histogram equalization and noise reduction filters. Then, the second step proceeds to eliminate the parts of the image having a texture different from that of the barchans dunes. Using supervised learning, we tested a coarse to fine textural analysis based on Kolomogorov Smirnov test and Youden’s J-statistic on co-occurrence matrix. As an output we obtained a mask that we used in the next step to reduce the search area. In the third step we used a gliding window on the mask and check SURF features with SVM to get barchans dunes candidates. Detected barchans dunes were considered as the fusion of overlapping candidates. The results of this approach were very satisfying in processing time and precision.

Scaling Analysis of Ocean Surface Turbulent Heterogeneities from Satellite Remote Sensing: Use of 2D Structure Functions.

Directory of Open Access Journals (Sweden)

P R Renosh

Full Text Available Satellite remote sensing observations allow the ocean surface to be sampled synoptically over large spatio-temporal scales. The images provided from visible and thermal infrared satellite observations are widely used in physical, biological, and ecological oceanography. The present work proposes a method to understand the multi-scaling properties of satellite products such as the Chlorophyll-a (Chl-a, and the Sea Surface Temperature (SST, rarely studied. The specific objectives of this study are to show how the small scale heterogeneities of satellite images can be characterised using tools borrowed from the fields of turbulence. For that purpose, we show how the structure function, which is classically used in the frame of scaling time series analysis, can be used also in 2D. The main advantage of this method is that it can be applied to process images which have missing data. Based on both simulated and real images, we demonstrate that coarse-graining (CG of a gradient modulus transform of the original image does not provide correct scaling exponents. We show, using a fractional Brownian simulation in 2D, that the structure function (SF can be used with randomly sampled couple of points, and verify that 1 million of couple of points provides enough statistics.

NASA Goddards LiDAR, Hyperspectral and Thermal (G-LiHT) Airborne Imager

Science.gov (United States)

Cook, Bruce D.; Corp, Lawrence A.; Nelson, Ross F.; Middleton, Elizabeth M.; Morton, Douglas C.; McCorkel, Joel T.; Masek, Jeffrey G.; Ranson, Kenneth J.; Ly, Vuong; Montesano, Paul M.

2013-01-01

The combination of LiDAR and optical remotely sensed data provides unique information about ecosystem structure and function. Here, we describe the development, validation and application of a new airborne system that integrates commercial off the shelf LiDAR hyperspectral and thermal components in a compact, lightweight and portable system. Goddard's LiDAR, Hyperspectral and Thermal (G-LiHT) airborne imager is a unique system that permits simultaneous measurements of vegetation structure, foliar spectra and surface temperatures at very high spatial resolution (approximately 1 m) on a wide range of airborne platforms. The complementary nature of LiDAR, optical and thermal data provide an analytical framework for the development of new algorithms to map plant species composition, plant functional types, biodiversity, biomass and carbon stocks, and plant growth. In addition, G-LiHT data enhance our ability to validate data from existing satellite missions and support NASA Earth Science research. G-LiHT's data processing and distribution system is designed to give scientists open access to both low- and high-level data products (http://gliht.gsfc.nasa.gov), which will stimulate the community development of synergistic data fusion algorithms. G-LiHT has been used to collect more than 6,500 km2 of data for NASA-sponsored studies across a broad range of ecoregions in the USA and Mexico. In this paper, we document G-LiHT design considerations, physical specifications, instrument performance and calibration and acquisition parameters. In addition, we describe the data processing system and higher-level data products that are freely distributed under NASA's Data and Information policy.

Long-distance thermal temporal ghost imaging over optical fibers

Science.gov (United States)

Yao, Xin; Zhang, Wei; Li, Hao; You, Lixing; Wang, Zhen; Huang, Yidong

2018-02-01

A thermal ghost imaging scheme between two distant parties is proposed and experimentally demonstrated over long-distance optical fibers. In the scheme, the weak thermal light is split into two paths. Photons in one path are spatially diffused according to their frequencies by a spatial dispersion component, then illuminate the object and record its spatial transmission information. Photons in the other path are temporally diffused by a temporal dispersion component. By the coincidence measurement between photons of two paths, the object can be imaged in a way of ghost imaging, based on the frequency correlation between photons in the two paths. In the experiment, the weak thermal light source is prepared by the spontaneous four-wave mixing in a silicon waveguide. The temporal dispersion is introduced by single mode fibers of 50 km, which also could be looked as a fiber link. Experimental results show that this scheme can be realized over long-distance optical fibers.

PROBLEMS AND LIMITATIONS OF SATELLITE IMAGE ORIENTATION FOR DETERMINATION OF HEIGHT MODELS

Directory of Open Access Journals (Sweden)

K. Jacobsen

2017-05-01

Full Text Available The usual satellite image orientation is based on bias corrected rational polynomial coefficients (RPC. The RPC are describing the direct sensor orientation of the satellite images. The locations of the projection centres today are without problems, but an accuracy limit is caused by the attitudes. Very high resolution satellites today are very agile, able to change the pointed area over 200km within 10 to 11 seconds. The corresponding fast attitude acceleration of the satellite may cause a jitter which cannot be expressed by the third order RPC, even if it is recorded by the gyros. Only a correction of the image geometry may help, but usually this will not be done. The first indication of jitter problems is shown by systematic errors of the y-parallaxes (py for the intersection of corresponding points during the computation of ground coordinates. These y-parallaxes have a limited influence to the ground coordinates, but similar problems can be expected for the x-parallaxes, determining directly the object height. Systematic y-parallaxes are shown for Ziyuan-3 (ZY3, WorldView-2 (WV2, Pleiades, Cartosat-1, IKONOS and GeoEye. Some of them have clear jitter effects. In addition linear trends of py can be seen. Linear trends in py and tilts in of computed height models may be caused by limited accuracy of the attitude registration, but also by bias correction with affinity transformation. The bias correction is based on ground control points (GCPs. The accuracy of the GCPs usually does not cause some limitations but the identification of the GCPs in the images may be difficult. With 2-dimensional bias corrected RPC-orientation by affinity transformation tilts of the generated height models may be caused, but due to large affine image deformations some satellites, as Cartosat-1, have to be handled with bias correction by affinity transformation. Instead of a 2-dimensional RPC-orientation also a 3-dimensional orientation is possible, respecting the

Problems and Limitations of Satellite Image Orientation for Determination of Height Models

Science.gov (United States)

Jacobsen, K.

2017-05-01

The usual satellite image orientation is based on bias corrected rational polynomial coefficients (RPC). The RPC are describing the direct sensor orientation of the satellite images. The locations of the projection centres today are without problems, but an accuracy limit is caused by the attitudes. Very high resolution satellites today are very agile, able to change the pointed area over 200km within 10 to 11 seconds. The corresponding fast attitude acceleration of the satellite may cause a jitter which cannot be expressed by the third order RPC, even if it is recorded by the gyros. Only a correction of the image geometry may help, but usually this will not be done. The first indication of jitter problems is shown by systematic errors of the y-parallaxes (py) for the intersection of corresponding points during the computation of ground coordinates. These y-parallaxes have a limited influence to the ground coordinates, but similar problems can be expected for the x-parallaxes, determining directly the object height. Systematic y-parallaxes are shown for Ziyuan-3 (ZY3), WorldView-2 (WV2), Pleiades, Cartosat-1, IKONOS and GeoEye. Some of them have clear jitter effects. In addition linear trends of py can be seen. Linear trends in py and tilts in of computed height models may be caused by limited accuracy of the attitude registration, but also by bias correction with affinity transformation. The bias correction is based on ground control points (GCPs). The accuracy of the GCPs usually does not cause some limitations but the identification of the GCPs in the images may be difficult. With 2-dimensional bias corrected RPC-orientation by affinity transformation tilts of the generated height models may be caused, but due to large affine image deformations some satellites, as Cartosat-1, have to be handled with bias correction by affinity transformation. Instead of a 2-dimensional RPC-orientation also a 3-dimensional orientation is possible, respecting the object height

Thermal imaging of spin Peltier effect

Science.gov (United States)

Daimon, Shunsuke; Iguchi, Ryo; Hioki, Tomosato; Saitoh, Eiji; Uchida, Ken-Ichi

2016-12-01

The Peltier effect modulates the temperature of a junction comprising two different conductors in response to charge currents across the junction, which is used in solid-state heat pumps and temperature controllers in electronics. Recently, in spintronics, a spin counterpart of the Peltier effect was observed. The `spin Peltier effect' modulates the temperature of a magnetic junction in response to spin currents. Here we report thermal imaging of the spin Peltier effect; using active thermography technique, we visualize the temperature modulation induced by spin currents injected into a magnetic insulator from an adjacent metal. The thermal images reveal characteristic distribution of spin-current-induced heat sources, resulting in the temperature change confined only in the vicinity of the metal/insulator interface. This finding allows us to estimate the actual magnitude of the temperature modulation induced by the spin Peltier effect, which is more than one order of magnitude greater than previously believed.

Occupancy Analysis of Sports Arenas Using Thermal Imaging

DEFF Research Database (Denmark)

Gade, Rikke; Jørgensen, Anders; Moeslund, Thomas B.

2012-01-01

This paper presents a system for automatic analysis of the occupancy of sports arenas. By using a thermal camera for image capturing the number of persons and their location on the court are found without violating any privacy issues. The images are binarised with an automatic threshold method...

Thematic mapping from satellite imagery

CERN Document Server

Denègre, J

2013-01-01

Thematic Mapping from Satellite Imagery: A Guidebook discusses methods in producing maps using satellite images. The book is comprised of five chapters; each chapter covers one stage of the process. Chapter 1 tackles the satellite remote sensing imaging and its cartographic significance. Chapter 2 discusses the production processes for extracting information from satellite data. The next chapter covers the methods for combining satellite-derived information with that obtained from conventional sources. Chapter 4 deals with design and semiology for cartographic representation, and Chapter 5 pre

Evolutionary design of a satellite thermal control system: Real experiments for a CubeSat mission

International Nuclear Information System (INIS)

Escobar, Emanuel; Diaz, Marcos; Zagal, Juan Cristóbal

2016-01-01

Highlights: • GAs applied to automate design of CubeSat passive thermal control system (coating). • Simulation adapted with real physical data (mockup experiment in vacuum chamber). • Obtained coating patterns consistently outperform engineered solutions (by 5 K). • Evolved coating patterns are far superior (by 8 K) than unpainted aluminum. - Abstract: This paper studies the use of artificial evolution to automate the design of a satellite passive thermal control system. This type of adaptation often requires the use of computer simulations to evaluate fitness of a large number of candidate solutions. Simulations are required to be expedient and accurate so that solutions can be successfully transferred to reality. We explore a design process that involves three steps. On a first step candidate solutions (implemented as surface paint tiling patterns) are tested using a FEM model and ranked according to their quality to meet mission temperature requirements. On a second step the best individual is implemented as a real physical satellite mockup and tested inside a vacuum chamber, having light sources imitating the effect of solar light. On a third step the simulation model is adapted with data obtained during the real evaluation. These updated models can be further employed for continuing genetic search. Current differences between our simulation and our real physical setup are in the order of 1.45 K mean squared error for faces pointing toward the light source and 2.4 K mean squared errors for shadowed faces. We found that evolved tiling patterns can be 5 K below engineered patterns and 8 K below using unpainted aluminum satellite surfaces.

Monitoring of Siberian biomass burning smoke from AHI on board geostationary satellite Himawari-8

Science.gov (United States)

Sano, I.; Mukai, S.; Yoshida, A.; Nakata, M.; Minoura, H.; Holben, B. N.

2016-12-01

High frequency aerosol measurements are demanded for evaluation of the model simulations, monitoring the atmospheric qualities such as Particulate Matter (PM2.5), and so on. Geostationary satellite provides us with the high frequency information of the atmosphere. Japanese Meteorological Agency (JMA) launched the Himawari-8 geostationary satellite in 2014 and has prepared Himawari-9 for launching in 2016. Both satellites carry new generation imagers named Advanced Himawari Imager (AHI). They have 16 multi-channels from short visible to thermal infrared wavelengths with 1 km IFOV for visible and 2 km for infrared. Each observation is done within 10 minutes for the Earth full disk. Then high frequency Earth observations are realized. AHI has frequently observed biomass burning plume around East Siberia and its transportation according to weather system. This work retrieves aerosol properties due to the Siberian smoke plume and its movements based on the measurements with AHI. The results are compared with ground based measurements which have newly deployed at an AERONET/Niigata site in Japan. It is shown here that continuous measurements of aerosols from geostationary satellite combination with the polar orbiting satellite provide us with much detail information of aerosol.

New Satellite Estimates of Mixed-Phase Cloud Properties: A Synergistic Approach for Application to Global Satellite Imager Data

Science.gov (United States)

Smith, W. L., Jr.; Spangenberg, D.; Fleeger, C.; Sun-Mack, S.; Chen, Y.; Minnis, P.

2016-12-01

Determining accurate cloud properties horizontally and vertically over a full range of time and space scales is currently next to impossible using data from either active or passive remote sensors or from modeling systems. Passive satellite imagers provide horizontal and temporal resolution of clouds, but little direct information on vertical structure. Active sensors provide vertical resolution but limited spatial and temporal coverage. Cloud models embedded in NWP can produce realistic clouds but often not at the right time or location. Thus, empirical techniques that integrate information from multiple observing and modeling systems are needed to more accurately characterize clouds and their impacts. Such a strategy is employed here in a new cloud water content profiling technique developed for application to satellite imager cloud retrievals based on VIS, IR and NIR radiances. Parameterizations are developed to relate imager retrievals of cloud top phase, optical depth, effective radius and temperature to ice and liquid water content profiles. The vertical structure information contained in the parameterizations is characterized climatologically from cloud model analyses, aircraft observations, ground-based remote sensing data, and from CloudSat and CALIPSO. Thus, realistic cloud-type dependent vertical structure information (including guidance on cloud phase partitioning) circumvents poor assumptions regarding vertical homogeneity that plague current passive satellite retrievals. This paper addresses mixed phase cloud conditions for clouds with glaciated tops including those associated with convection and mid-latitude storm systems. Novel outcomes of our approach include (1) simultaneous retrievals of ice and liquid water content and path, which are validated with active sensor, microwave and in-situ data, and yield improved global cloud climatologies, and (2) new estimates of super-cooled LWC, which are demonstrated in aviation safety applications and

Urban thermal environment and its biophysical parameters derived from satellite remote sensing imagery

Science.gov (United States)

Zoran, Maria A.; Savastru, Roxana S.; Savastru, Dan M.; Tautan, Marina N.; Baschir, Laurentiu V.

2013-10-01

In frame of global warming, the field of urbanization and urban thermal environment are important issues among scientists all over the world. This paper investigated the influences of urbanization on urban thermal environment as well as the relationships of thermal characteristics to other biophysical variables in Bucharest metropolitan area of Romania based on satellite remote sensing imagery Landsat TM/ETM+, time series MODIS Terra/Aqua data and IKONOS acquired during 1990 - 2012 period. Vegetation abundances and percent impervious surfaces were derived by means of linear spectral mixture model, and a method for effectively enhancing impervious surface has been developed to accurately examine the urban growth. The land surface temperature (Ts), a key parameter for urban thermal characteristics analysis, was also retrieved from thermal infrared band of Landsat TM/ETM+, from MODIS Terra/Aqua datasets. Based on these parameters, the urban growth, urban heat island effect (UHI) and the relationships of Ts to other biophysical parameters have been analyzed. Results indicated that the metropolitan area ratio of impervious surface in Bucharest increased significantly during two decades investigated period, the intensity of urban heat island and heat wave events being most significant. The correlation analyses revealed that, at the pixel-scale, Ts possessed a strong positive correlation with percent impervious surfaces and negative correlation with vegetation abundances at the regional scale, respectively. This analysis provided an integrated research scheme and the findings can be very useful for urban ecosystem modeling.

Reliability of a novel thermal imaging system for temperature assessment of healthy feet.

Science.gov (United States)

Petrova, N L; Whittam, A; MacDonald, A; Ainarkar, S; Donaldson, A N; Bevans, J; Allen, J; Plassmann, P; Kluwe, B; Ring, F; Rogers, L; Simpson, R; Machin, G; Edmonds, M E

2018-01-01

Thermal imaging is a useful modality for identifying preulcerative lesions ("hot spots") in diabetic foot patients. Despite its recognised potential, at present, there is no readily available instrument for routine podiatric assessment of patients at risk. To address this need, a novel thermal imaging system was recently developed. This paper reports the reliability of this device for temperature assessment of healthy feet. Plantar skin foot temperatures were measured with the novel thermal imaging device (Diabetic Foot Ulcer Prevention System (DFUPS), constructed by Photometrix Imaging Ltd) and also with a hand-held infrared spot thermometer (Thermofocus® 01500A3, Tecnimed, Italy) after 20 min of barefoot resting with legs supported and extended in 105 subjects (52 males and 53 females; age range 18 to 69 years) as part of a multicentre clinical trial. The temperature differences between the right and left foot at five regions of interest (ROIs), including 1st and 4th toes, 1st, 3rd and 5th metatarsal heads were calculated. The intra-instrument agreement (three repeated measures) and the inter-instrument agreement (hand-held thermometer and thermal imaging device) were quantified using intra-class correlation coefficients (ICCs) and the 95% confidence intervals (CI). Both devices showed almost perfect agreement in replication by instrument. The intra-instrument ICCs for the thermal imaging device at all five ROIs ranged from 0.95 to 0.97 and the intra-instrument ICCs for the hand-held-thermometer ranged from 0.94 to 0.97. There was substantial to perfect inter-instrument agreement between the hand-held thermometer and the thermal imaging device and the ICCs at all five ROIs ranged between 0.94 and 0.97. This study reports the performance of a novel thermal imaging device in the assessment of foot temperatures in healthy volunteers in comparison with a hand-held infrared thermometer. The newly developed thermal imaging device showed very good agreement in

Review On Feasibility of Using Satellite Imaging for Risk Management of Derailment Related Turnout Component Failures

Science.gov (United States)

Dindar, Serdar; Kaewunruen, Sakdirat; Osman, Mohd H.

2017-10-01

One of the emerging significant advances in engineering, satellite imaging (SI) is becoming very common in any kind of civil engineering projects e.g., bridge, canal, dam, earthworks, power plant, water works etc., to provide an accurate, economical and expeditious means of acquiring a rapid assessment. Satellite imaging services in general utilise combinations of high quality satellite imagery, image processing and interpretation to obtain specific required information, e.g. surface movement analysis. To extract, manipulate and provide such a precise knowledge, several systems, including geographic information systems (GIS) and global positioning system (GPS), are generally used for orthorectification. Although such systems are useful for mitigating risk from projects, their productiveness is arguable and operational risk after application is open to discussion. As the applicability of any novel application to the railway industry is often measured in terms of whether or not it has gained in-depth knowledge and to what degree, as a result of errors during its operation, this novel application generates risk in ongoing projects. This study reviews what can be achievable for risk management of railway turnouts thorough satellite imaging. The methodology is established on the basis of other published articles in this area and the results of applications to understand how applicable such imagining process is on railway turnouts, and how sub-systems in turnouts can be effectively traced/operated with less risk than at present. As a result of this review study, it is aimed that the railway sector better understands risk mitigation in particular applications.

Thermal imaging in screening of joint inflammation and rheumatoid arthritis in children

International Nuclear Information System (INIS)

Lasanen, R; Julkunen, P; Töyräs, J; Piippo-Savolainen, E; Remes-Pakarinen, T; Kröger, L; Heikkilä, A; Karhu, J

2015-01-01

Potential of modern thermal imaging for screening and differentiation of joint inflammation has not been assessed in child and juvenile patient populations, typically demanding groups in diagnostics of musculoskeletal disorders. We hypothesize that thermal imaging can detect joint inflammation in patients with juvenile idiopathic arthritis or autoimmune disease with arthritis such as systemic lupus erythematosus. To evaluate the hypothesis, we studied 58 children exhibiting symptoms of joint inflammation. First, the patients’ joints were examined along clinical procedure supplemented with ultrasound imaging when deemed necessary by the clinician. Second, thermal images were acquired from patients’ knees and ankles. Results of thermal imaging were compared to clinical evaluations in knee and ankle. The temperatures were significantly (p max = 0.044, p mean  < 0.001) higher in inflamed ankle joints, but not in inflamed knee joints. No significant difference was found between the skin surface temperatures of medial and lateral aspects of ankle joints. In knee joints the mean temperatures of medial and lateral aspect differed significantly (p = 0.004). We have demonstrated that thermal imaging may have potential for detecting joint inflammation in ankle joints of children. For knee joints our results are inconclusive and further research is warranted. (paper)

Visualization and measurement by image processing of thermal hydraulic phenomena by neutron radiography

International Nuclear Information System (INIS)

Takenaka, Nobuyuki

1996-01-01

Neutron Radiography was applied to visualization of thermal hydraulic phenomena and measurement was carried out by image processing the visualized images. Since attenuation of thermal neutron rays is high in ordinary liquids like water and organic fluid while it is low in most of metals, liquid flow behaviors can be visualized through a metallic wall by neutron radiography. Measurement of void fraction and flow vector field which is important to study thermal hydraulic phenomena can be carried out by image processing the images obtained by the visualization. Various two-phase and liquid metal flows were visualized by a JRR-3M thermal neutron radiography system in the present study. Multi-dimensional void fraction distributions in two-phase flows and flow vector fields in liquid metals, which are difficult to measure by the other methods, were successfully measured by image processing. It was shown that neutron radiography was efficiently applicable to study thermal hydraulic phenomena. (author)

Regional thermal patterns in Portugal using satellite images (NOAA AVHRR

Directory of Open Access Journals (Sweden)

António Lopes

1995-06-01

Full Text Available In this paper two NOAA AVHRR diurnal images (channel 4 are used to determine the required procedures aiming at a future operational analysis system in Portugal. Preprocessing and classification operations are described. Strong correlation between air and surface temperature is verified and rather detailed air temperature patterns can be inferred.

Environmental Testing Philosophy for a Sandia National Laboratories' Small Satellite Project - A Retrospective

Energy Technology Data Exchange (ETDEWEB)

CAP,JEROME S.

2000-08-24

Sandia has recently completed the flight certification test series for the Multi-Spectral Thermal Imaging satellite (MTI), which is a small satellite for which Sandia was the system integrator. A paper was presented at the 16th Aerospace Testing Seminar discussing plans for performing the structural dynamics certification program for that satellite. The testing philosophy was originally based on a combination of system level vibroacoustic tests and component level shock and vibration tests. However, the plans evolved to include computational analyses using both Finite Element Analysis and Statistical Energy Analysis techniques. This paper outlines the final certification process and discuss lessons learned including both things that went well and things that should/could have been done differently.

Lava flows and cinder cones at Barren Island volcano, India (2005-2017): a spatio-temporal analysis using satellite images

Science.gov (United States)

Martha, Tapas R.; Roy, Priyom; Vinod Kumar, K.

2018-02-01

Barren Island volcano erupted during January-February 2017. Located near the Andaman trench and over a subduction zone, it is the only active volcano in India. It comprises a prominent caldera within which there is a polygenetic intra-caldera cinder cone system, with a record of eruptive events which date back to eighteenth century (1787-1832). Major eruptions occurred in 1991, 1994-1995, 2005 and, since 2008, the volcano has been showing near continuous activity with periodic eruptions. We used coarse spatial resolution "fire" products (Band I4) from Suomi National Polar-Orbiting Partnership Visible Infrared Imaging Radiometer Suite to detect days of eruption during the January-February 2017 period. Moderate spatial resolution (23.5 m) short-wavelength infrared (SWIR) data of Resourcesat-2 Linear Imaging Self Scanning Sensor-III available for specific days during this period were used to verify signatures of volcanic eruption. Thermal infrared band data from the Landsat series over the 2005-2017 periods were used to estimate the brightness temperature and location of the active vent within the polygenetic cinder cone field. High-spatial resolution images (1-5.8 m) in the visible bands (Resourcesat-2 LISS-IV, Cartosat-1 and 2) were used to delineate the changes in overall morphology of the volcano and to identify an inner crater ring fault, new paths of lava flow and the formation of a new cinder cone on the old crater. These multi-temporal data sets show significant changes in the paths of lava flows from 2005 to 2017. The observations also document periodic shifts in the location of effusive vents. Morphogenetic changes in recent eruptive phases of the Barren Island volcano were successfully delineated using a combination of multi-temporal and multi-resolution satellite images in visible, SWIR and thermal infrared regions of the electromagnetic spectrum.

Spatial and radiometric characterization of multi-spectrum satellite images through multi-fractal analysis

Science.gov (United States)

Alonso, Carmelo; Tarquis, Ana M.; Zúñiga, Ignacio; Benito, Rosa M.

2017-03-01

Several studies have shown that vegetation indexes can be used to estimate root zone soil moisture. Earth surface images, obtained by high-resolution satellites, presently give a lot of information on these indexes, based on the data of several wavelengths. Because of the potential capacity for systematic observations at various scales, remote sensing technology extends the possible data archives from the present time to several decades back. Because of this advantage, enormous efforts have been made by researchers and application specialists to delineate vegetation indexes from local scale to global scale by applying remote sensing imagery. In this work, four band images have been considered, which are involved in these vegetation indexes, and were taken by satellites Ikonos-2 and Landsat-7 of the same geographic location, to study the effect of both spatial (pixel size) and radiometric (number of bits coding the image) resolution on these wavelength bands as well as two vegetation indexes: the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI). In order to do so, a multi-fractal analysis of these multi-spectral images was applied in each of these bands and the two indexes derived. The results showed that spatial resolution has a similar scaling effect in the four bands, but radiometric resolution has a larger influence in blue and green bands than in red and near-infrared bands. The NDVI showed a higher sensitivity to the radiometric resolution than EVI. Both were equally affected by the spatial resolution. From both factors, the spatial resolution has a major impact in the multi-fractal spectrum for all the bands and the vegetation indexes. This information should be taken in to account when vegetation indexes based on different satellite sensors are obtained.

Coseismic displacements from SAR image offsets between different satellite sensors: Application to the 2001 Bhuj (India) earthquake

KAUST Repository

Wang, Teng

2015-09-05

Synthetic aperture radar (SAR) image offset tracking is increasingly being used for measuring ground displacements, e.g., due to earthquakes and landslide movement. However, this technique has been applied only to images acquired by the same or identical satellites. Here we propose a novel approach for determining offsets between images acquired by different satellite sensors, extending the usability of existing SAR image archives. The offsets are measured between two multiimage reflectivity maps obtained from different SAR data sets, which provide significantly better results than with single preevent and postevent images. Application to the 2001 Mw7.6 Bhuj earthquake reveals, for the first time, its near-field deformation using multiple preearthquake ERS and postearthquake Envisat images. The rupture model estimated from these cross-sensor offsets and teleseismic waveforms shows a compact fault slip pattern with fairly short rise times (<3 s) and a large stress drop (20 MPa), explaining the intense shaking observed in the earthquake.

Enhance wound healing monitoring through a thermal imaging based smartphone app

Science.gov (United States)

Yi, Steven; Lu, Minta; Yee, Adam; Harmon, John; Meng, Frank; Hinduja, Saurabh

2018-03-01

In this paper, we present a thermal imaging based app to augment traditional appearance based wound growth monitoring. Accurate diagnose and track of wound healing enables physicians to effectively assess, document, and individualize the treatment plan given to each wound patient. Currently, wounds are primarily examined by physicians through visual appearance and wound area. However, visual information alone cannot present a complete picture on a wound's condition. In this paper, we use a smartphone attached thermal imager and evaluate its effectiveness on augmenting visual appearance based wound diagnosis. Instead of only monitoring wound temperature changes on a wound, our app presents physicians a comprehensive measurements including relative temperature, wound healing thermal index, and wound blood flow. Through the rat wound experiments and by monitoring the integrated thermal measurements over 3 weeks of time frame, our app is able to show the underlying healing process through the blood flow. The implied significance of our app design and experiment includes: (a) It is possible to use a low cost smartphone attached thermal imager for added value on wound assessment, tracking, and treatment; and (b) Thermal mobile app can be used for remote wound healing assessment for mobile health based solution.

Assessing regional crop water demand using a satellite-based combination equation with a land surface temperature componen

DEFF Research Database (Denmark)

Moyano, Carmen; Garcia, Monica; Tornos, Lucia

2015-01-01

-sequence spanning for more than a decade (2002-2013). The thermal-PT-JPL model was forced with vegetation, albedo, reflectance and temperature products from the Moderate-resolution Imaging Spectroradiometer (MODIS) from both Aqua and Terra satellites. The study region, B-XII Irrigation District of the Lower...

Fourier-transform ghost imaging with pure far-field correlated thermal light

International Nuclear Information System (INIS)

Liu Honglin; Shen Xia; Han Shensheng; Zhu Daming

2007-01-01

Pure far-field correlated thermal light beams are created with phase grating, and Fourier-transform ghost imaging depending only on the far-field correlation is demonstrated experimentally. Theoretical analysis and the results of experimental investigation of this pure far-field correlated thermal light are presented. Applications which may be exploited with this imaging scheme are discussed

Mapping of Polar Areas Based on High-Resolution Satellite Images: The Example of the Henryk Arctowski Polish Antarctic Station

Science.gov (United States)

Kurczyński, Zdzisław; Różycki, Sebastian; Bylina, Paweł

2017-12-01

To produce orthophotomaps or digital elevation models, the most commonly used method is photogrammetric measurement. However, the use of aerial images is not easy in polar regions for logistical reasons. In these areas, remote sensing data acquired from satellite systems is much more useful. This paper presents the basic technical requirements of different products which can be obtain (in particular orthoimages and digital elevation model (DEM)) using Very-High-Resolution Satellite (VHRS) images. The study area was situated in the vicinity of the Henryk Arctowski Polish Antarctic Station on the Western Shore of Admiralty Bay, King George Island, Western Antarctic. Image processing was applied on two triplets of images acquired by the Pléiades 1A and 1B in March 2013. The results of the generation of orthoimages from the Pléiades systems without control points showed that the proposed method can achieve Root Mean Squared Error (RMSE) of 3-9 m. The presented Pléiades images are useful for thematic remote sensing analysis and processing of measurements. Using satellite images to produce remote sensing products for polar regions is highly beneficial and reliable and compares well with more expensive airborne photographs or field surveys.

Determination of the Impact of Urbanization on Agricultural Lands using Multi-temporal Satellite Sensor Images

Science.gov (United States)

Kaya, S.; Alganci, U.; Sertel, E.; Ustundag, B.

2015-12-01

Throughout the history, agricultural activities have been performed close to urban areas. Main reason behind this phenomenon is the need of fast marketing of the agricultural production to urban residents and financial provision. Thus, using the areas nearby cities for agricultural activities brings out advantage of easy transportation of productions and fast marketing. For decades, heavy migration to cities has directly and negatively affected natural grasslands, forests and agricultural lands. This pressure has caused agricultural lands to be changed into urban areas. Dense urbanization causes increase in impervious surfaces, heat islands and many other problems in addition to destruction of agricultural lands. Considering the negative impacts of urbanization on agricultural lands and natural resources, a periodic monitoring of these changes becomes indisputably important. At this point, satellite images are known to be good data sources for land cover / use change monitoring with their fast data acquisition, large area coverages and temporal resolution properties. Classification of the satellite images provides thematic the land cover / use maps of the earth surface and changes can be determined with GIS based analysis multi-temporal maps. In this study, effects of heavy urbanization over agricultural lands in Istanbul, metropolitan city of Turkey, were investigated with use of multi-temporal Landsat TM satellite images acquired between 1984 and 2011. Images were geometrically registered to each other and classified using supervised maximum likelihood classification algorithm. Resulting thematic maps were exported to GIS environment and destructed agricultural lands by urbanization were determined using spatial analysis.

Two-dimensional fruit ripeness estimation using thermal imaging

Science.gov (United States)

Sumriddetchkajorn, Sarun; Intaravanne, Yuttana

2013-06-01

Some green fruits do not change their color from green to yellow when being ripe. As a result, ripeness estimation via color and fluorescent analytical approaches cannot be applied. In this article, we propose and show for the first time how a thermal imaging camera can be used to two-dimensionally classify fruits into different ripeness levels. Our key idea relies on the fact that the mature fruits have higher heat capacity than the immature ones and therefore the change in surface temperature overtime is slower. Our experimental proof of concept using a thermal imaging camera shows a promising result in non-destructively identifying three different ripeness levels of mangoes Mangifera indica L.

Design and development of a very high resolution thermal imager

Science.gov (United States)

Kuerbitz, Gunther; Duchateau, Ruediger

1998-10-01

The design goal of this project was to develop a thermal imaging system with ultimate geometrical resolution without sacrificing thermal sensitivity. It was necessary to fulfil the criteria for a future advanced video standard. This video standard is the so-called HDTV standard (HDTV High Definition TeleVision). The thermal imaging system is a parallel scanning system working in the 7...11 micrometer spectral region. The detector for that system has to have 576 X n (n number of TDI stages) detector elements taking into account a twofold interlace. It must be carefully optimized in terms of range performance and size of optics entrance pupil as well as producibility and yield. This was done in strong interaction with the detector manufacturer. The 16:9 aspect ratio of the HDTV standard together with the high number of 1920 pixels/line impose high demands on the scanner design in terms of scan efficiency and linearity. As an advanced second generation thermal imager the system has an internal thermal reference. The electronics is fully digitized and comprises circuits for Non Uniformity Correction (NUC), scan conversion, electronic zoom, auto gain and level, edge enhancement, up/down and left/right reversion etc. It can be completely remote-controlled via a serial interface.

Spatial, Temporal and Spectral Satellite Image Fusion via Sparse Representation

Science.gov (United States)

Song, Huihui

Remote sensing provides good measurements for monitoring and further analyzing the climate change, dynamics of ecosystem, and human activities in global or regional scales. Over the past two decades, the number of launched satellite sensors has been increasing with the development of aerospace technologies and the growing requirements on remote sensing data in a vast amount of application fields. However, a key technological challenge confronting these sensors is that they tradeoff between spatial resolution and other properties, including temporal resolution, spectral resolution, swath width, etc., due to the limitations of hardware technology and budget constraints. To increase the spatial resolution of data with other good properties, one possible cost-effective solution is to explore data integration methods that can fuse multi-resolution data from multiple sensors, thereby enhancing the application capabilities of available remote sensing data. In this thesis, we propose to fuse the spatial resolution with temporal resolution and spectral resolution, respectively, based on sparse representation theory. Taking the study case of Landsat ETM+ (with spatial resolution of 30m and temporal resolution of 16 days) and MODIS (with spatial resolution of 250m ~ 1km and daily temporal resolution) reflectance, we propose two spatial-temporal fusion methods to combine the fine spatial information of Landsat image and the daily temporal resolution of MODIS image. Motivated by that the images from these two sensors are comparable on corresponding bands, we propose to link their spatial information on available Landsat- MODIS image pair (captured on prior date) and then predict the Landsat image from the MODIS counterpart on prediction date. To well-learn the spatial details from the prior images, we use a redundant dictionary to extract the basic representation atoms for both Landsat and MODIS images based on sparse representation. Under the scenario of two prior Landsat

Image Quality Assessment of High-Resolution Satellite Images with Mtf-Based Fuzzy Comprehensive Evaluation Method

Science.gov (United States)

Wu, Z.; Luo, Z.; Zhang, Y.; Guo, F.; He, L.

2018-04-01

A Modulation Transfer Function (MTF)-based fuzzy comprehensive evaluation method was proposed in this paper for the purpose of evaluating high-resolution satellite image quality. To establish the factor set, two MTF features and seven radiant features were extracted from the knife-edge region of image patch, which included Nyquist, MTF0.5, entropy, peak signal to noise ratio (PSNR), average difference, edge intensity, average gradient, contrast and ground spatial distance (GSD). After analyzing the statistical distribution of above features, a fuzzy evaluation threshold table and fuzzy evaluation membership functions was established. The experiments for comprehensive quality assessment of different natural and artificial objects was done with GF2 image patches. The results showed that the calibration field image has the highest quality scores. The water image has closest image quality to the calibration field, quality of building image is a little poor than water image, but much higher than farmland image. In order to test the influence of different features on quality evaluation, the experiment with different weights were tested on GF2 and SPOT7 images. The results showed that different weights correspond different evaluating effectiveness. In the case of setting up the weights of edge features and GSD, the image quality of GF2 is better than SPOT7. However, when setting MTF and PSNR as main factor, the image quality of SPOT7 is better than GF2.

Utilizing Structure-from-Motion Photogrammetry with Airborne Visual and Thermal Images to Monitor Thermal Areas in Yellowstone National Park

Science.gov (United States)

Carr, B. B.; Vaughan, R. G.

2017-12-01

The thermal areas in Yellowstone National Park (Wyoming, USA) are constantly changing. Persistent monitoring of these areas is necessary to better understand the behavior and potential hazards of both the thermal features and the deeper hydrothermal system driving the observed surface activity. As part of the Park's monitoring program, thousands of visual and thermal infrared (TIR) images have been acquired from a variety of airborne platforms over the past decade. We have used structure-from-motion (SfM) photogrammetry techniques to generate a variety of data products from these images, including orthomosaics, temperature maps, and digital elevation models (DEMs). Temperature maps were generated for Upper Geyser Basin and Norris Geyser Basin for the years 2009-2015, by applying SfM to nighttime TIR images collected from an aircraft-mounted forward-looking infrared (FLIR) camera. Temperature data were preserved through the SfM processing by applying a uniform linear stretch over the entire image set to convert between temperature and a 16-bit digital number. Mosaicked temperature maps were compared to the original FLIR image frames and to ground-based temperature data to constrain the accuracy of the method. Due to pixel averaging and resampling, among other issues, the derived temperature values are typically within 5-10 ° of the values of the un-resampled image frame. We also created sub-meter resolution DEMs from airborne daytime visual images of individual thermal areas. These DEMs can be used for resource and hazard management, and in cases where multiple DEMs exist from different times, for measuring topographic change, including change due to thermal activity. For example, we examined the sensitivity of the DEMs to topographic change by comparing DEMs of the travertine terraces at Mammoth Hot Springs, which can grow at > 1 m per year. These methods are generally applicable to images from airborne platforms, including planes, helicopters, and unmanned aerial

Thickness measurement by two-sided step-heating thermal imaging

Science.gov (United States)

Li, Xiaoli; Tao, Ning; Sun, J. G.; Zhang, Cunlin; Zhao, Yuejin

2018-01-01

Infrared thermal imaging is a promising nondestructive technique for thickness prediction. However, it is usually thought to be only appropriate for testing the thickness of thin objects or near-surface structures. In this study, we present a new two-sided step-heating thermal imaging method which employed a low-cost portable halogen lamp as the heating source and verified it with two stainless steel step wedges with thicknesses ranging from 5 mm to 24 mm. We first derived the one-dimensional step-heating thermography theory with the consideration of warm-up time of the lamp, and then applied the nonlinear regression method to fit the experimental data by the derived function to determine the thickness. After evaluating the reliability and accuracy of the experimental results, we concluded that this method is capable of testing thick objects. In addition, we provided the criterions for both the required data length and the applicable thickness range of the testing material. It is evident that this method will broaden the thermal imaging application for thickness measurement.

Satellite image analysis and a hybrid ESSS/ANN model to forecast solar irradiance in the tropics

International Nuclear Information System (INIS)

Dong, Zibo; Yang, Dazhi; Reindl, Thomas; Walsh, Wilfred M.

2014-01-01

Highlights: • Satellite image analysis is performed and cloud cover index is classified using self-organizing maps (SOM). • The ESSS model is used to forecast cloud cover index. • Solar irradiance is estimated using multi-layer perceptron (MLP). • The proposed model shows better accuracy than other investigated models. - Abstract: We forecast hourly solar irradiance time series using satellite image analysis and a hybrid exponential smoothing state space (ESSS) model together with artificial neural networks (ANN). Since cloud cover is the major factor affecting solar irradiance, cloud detection and classification are crucial to forecast solar irradiance. Geostationary satellite images provide cloud information, allowing a cloud cover index to be derived and analysed using self-organizing maps (SOM). Owing to the stochastic nature of cloud generation in tropical regions, the ESSS model is used to forecast cloud cover index. Among different models applied in ANN, we favour the multi-layer perceptron (MLP) to derive solar irradiance based on the cloud cover index. This hybrid model has been used to forecast hourly solar irradiance in Singapore and the technique is found to outperform traditional forecasting models

AN EVOLUTIONARY ALGORITHM FOR FAST INTENSITY BASED IMAGE MATCHING BETWEEN OPTICAL AND SAR SATELLITE IMAGERY

Directory of Open Access Journals (Sweden)

P. Fischer

2018-04-01

Full Text Available This paper presents a hybrid evolutionary algorithm for fast intensity based matching between satellite imagery from SAR and very high-resolution (VHR optical sensor systems. The precise and accurate co-registration of image time series and images of different sensors is a key task in multi-sensor image processing scenarios. The necessary preprocessing step of image matching and tie-point detection is divided into a search problem and a similarity measurement. Within this paper we evaluate the use of an evolutionary search strategy for establishing the spatial correspondence between satellite imagery of optical and radar sensors. The aim of the proposed algorithm is to decrease the computational costs during the search process by formulating the search as an optimization problem. Based upon the canonical evolutionary algorithm, the proposed algorithm is adapted for SAR/optical imagery intensity based matching. Extensions are drawn using techniques like hybridization (e.g. local search and others to lower the number of objective function calls and refine the result. The algorithm significantely decreases the computational costs whilst finding the optimal solution in a reliable way.

Integration of Satellite Tracking Data and Satellite Images for Detailed Characteristics of Wildlife Habitats

Science.gov (United States)

Dobrynin, D. V.; Rozhnov, V. V.; Saveliev, A. A.; Sukhova, O. V.; Yachmennikova, A. A.

2017-12-01

Methods of analysis of the results got from satellite tracking of large terrestrial mammals differ in the level of their integration with additional geographic data. The reliable fine-scale cartographic basis for assessing specific wildlife habitats can be developed through the interpretation of multispectral remote sensing data and extrapolation of the results to the entire estimated species range. Topographic maps were ordinated according to classified features using self-organizing maps (Kohonen's SOM). The satellite image of the Ussuriiskyi Nature Reserve area was interpreted for the analysis of movement conditions for seven wild Amur tigers ( Panthera tigris altaica) equipped with GPS collars. 225 SOM classes for cartographic visualization are sufficient for the detailed mapping of all natural complexes that were identified as a result of interpretation. During snow-free periods, tigers preferred deciduous and shrub associations at lower elevations, as well as mixed forests in the valleys of streams that are adjacent to sparse forests and shrub watershed in the mountain ranges; during heavy snow periods, the animals preferred the entire range of plant communities in different relief types, except for open sites in meadows and abandoned fields at foothills. The border zones of different biotopes were typically used by the tigers during all seasons. Amur tigers preferred coniferous forests for long-term movements.

Theoretical scheme of thermal-light many-ghost imaging by Nth-order intensity correlation

International Nuclear Information System (INIS)

Liu Yingchuan; Kuang Leman

2011-01-01

In this paper, we propose a theoretical scheme of many-ghost imaging in terms of Nth-order correlated thermal light. We obtain the Gaussian thin lens equations in the many-ghost imaging protocol. We show that it is possible to produce N-1 ghost images of an object at different places in a nonlocal fashion by means of a higher order correlated imaging process with an Nth-order correlated thermal source and correlation measurements. We investigate the visibility of the ghost images in the scheme and obtain the upper bounds of the visibility for the Nth-order correlated thermal-light ghost imaging. It is found that the visibility of the ghost images can be dramatically enhanced when the order of correlation becomes larger. It is pointed out that the many-ghost imaging phenomenon is an observable physical effect induced by higher order coherence or higher order correlations of optical fields.

One-dimensional thermal evolution calculation based on a mixing length theory: Application to Saturnian icy satellites

Science.gov (United States)

Kamata, S.

2017-12-01

Solid-state thermal convection plays a major role in the thermal evolution of solid planetary bodies. Solving the equation system for thermal evolution considering convection requires 2-D or 3-D modeling, resulting in large calculation costs. A 1-D calculation scheme based on mixing length theory (MLT) requires a much lower calculation cost and is suitable for parameter studies. A major concern for the MLT scheme is its accuracy due to a lack of detailed comparisons with higher dimensional schemes. In this study, I quantify its accuracy via comparisons of thermal profiles obtained by 1-D MLT and 3-D numerical schemes. To improve the accuracy, I propose a new definition of the mixing length (l), which is a parameter controlling the efficiency of heat transportation due to convection. Adopting this new definition of l, I investigate the thermal evolution of Dione and Enceladus under a wide variety of parameter conditions. Calculation results indicate that each satellite requires several tens of GW of heat to possess a 30-km-thick global subsurface ocean. Dynamical tides may be able to account for such an amount of heat, though their ices need to be highly viscous.

Development and Analysis of Image Registration Program for the Communication, Ocean, Meteorological Satellite (COMS

Directory of Open Access Journals (Sweden)

Un-Seob Lee

2007-09-01

Full Text Available We developed a software for simulations and analyses of the Image Navigation and Registration (INR system, and compares the characteristics of Image Motion Compensation (IMC algorithms for the INR system. According to the orbit errors and attitude errors, the capabilities of the image distortions are analyzed. The distortions of images can be compensated by GOES IMC algorithm and Modified IMC (MIMC algorithm. The capabilities of each IMC algorithm are confirmed based on compensated images. The MIMC yields better results than GOES IMC although both the algorithms well compensate distorted images. The results of this research can be used as valuable asset to design of INR system for the Communication, Ocean, Meteorological Satellite (COMS.

Digital Enhancement of Night Vision and Thermal Images

National Research Council Canada - National Science Library

Teo, Chek

2003-01-01

.... This thesis explores the effect of the Contrast Limited Adaptive Histogram Equalization (CLAHE) process on night vision and thermal images With better contrast, target detection and discrimination can be improved...

A graph-based approach to detect spatiotemporal dynamics in satellite image time series

Science.gov (United States)

Guttler, Fabio; Ienco, Dino; Nin, Jordi; Teisseire, Maguelonne; Poncelet, Pascal

2017-08-01

Enhancing the frequency of satellite acquisitions represents a key issue for Earth Observation community nowadays. Repeated observations are crucial for monitoring purposes, particularly when intra-annual process should be taken into account. Time series of images constitute a valuable source of information in these cases. The goal of this paper is to propose a new methodological framework to automatically detect and extract spatiotemporal information from satellite image time series (SITS). Existing methods dealing with such kind of data are usually classification-oriented and cannot provide information about evolutions and temporal behaviors. In this paper we propose a graph-based strategy that combines object-based image analysis (OBIA) with data mining techniques. Image objects computed at each individual timestamp are connected across the time series and generates a set of evolution graphs. Each evolution graph is associated to a particular area within the study site and stores information about its temporal evolution. Such information can be deeply explored at the evolution graph scale or used to compare the graphs and supply a general picture at the study site scale. We validated our framework on two study sites located in the South of France and involving different types of natural, semi-natural and agricultural areas. The results obtained from a Landsat SITS support the quality of the methodological approach and illustrate how the framework can be employed to extract and characterize spatiotemporal dynamics.

Geant4 Analysis of a Thermal Neutron Real-Time Imaging System

Science.gov (United States)

Datta, Arka; Hawari, Ayman I.

2017-07-01

Thermal neutron imaging is a technique for nondestructive testing providing complementary information to X-ray imaging for a wide range of applications in science and engineering. Advancement of electronic imaging systems makes it possible to obtain neutron radiographs in real time. This method requires a scintillator to convert neutrons to optical photons and a charge-coupled device (CCD) camera to detect those photons. Alongside, a well collimated beam which reduces geometrical blurriness, the use of a thin scintillator can improve the spatial resolution significantly. A representative scintillator that has been applied widely for thermal neutron imaging is 6LiF:ZnS (Ag). In this paper, a multiphysics simulation approach for designing thermal neutron imaging system is investigated. The Geant4 code is used to investigate the performance of a thermal neutron imaging system starting with a neutron source and including the production of charged particles and optical photons in the scintillator and their transport for image formation in the detector. The simulation geometry includes the neutron beam collimator and sapphire filter. The 6LiF:ZnS (Ag) scintillator is modeled along with a pixelated detector for image recording. The spatial resolution of the system was obtained as the thickness of the scintillator screen was varied between 50 and 400 μm. The results of the simulation were compared to experimental results, including measurements performed using the PULSTAR nuclear reactor imaging beam, showing good agreement. Using the established model, further examination showed that the resolution contribution of the scintillator screen is correlated with its thickness and the range of the neutron absorption reaction products (i.e., the alpha and triton particles). Consequently, thinner screens exhibit improved spatial resolution. However, this will compromise detection efficiency due to the reduced probability of neutron absorption.

Object localization in handheld thermal images for fireground understanding

Science.gov (United States)

Vandecasteele, Florian; Merci, Bart; Jalalvand, Azarakhsh; Verstockt, Steven

2017-05-01

Despite the broad application of the handheld thermal imaging cameras in firefighting, its usage is mostly limited to subjective interpretation by the person carrying the device. As remedies to overcome this limitation, object localization and classification mechanisms could assist the fireground understanding and help with the automated localization, characterization and spatio-temporal (spreading) analysis of the fire. An automated understanding of thermal images can enrich the conventional knowledge-based firefighting techniques by providing the information from the data and sensing-driven approaches. In this work, transfer learning is applied on multi-labeling convolutional neural network architectures for object localization and recognition in monocular visual, infrared and multispectral dynamic images. Furthermore, the possibility of analyzing fire scene images is studied and their current limitations are discussed. Finally, the understanding of the room configuration (i.e., objects location) for indoor localization in reduced visibility environments and the linking with Building Information Models (BIM) are investigated.

Evaluation of the AN/SAY-1 Thermal Imaging Sensor System

National Research Council Canada - National Science Library

Smith, John G; Middlebrook, Christopher T

2002-01-01

The AN/SAY-1 Thermal Imaging Sensor System "TISS" was developed to provide surface ships with a day/night imaging capability to detect low radar reflective, small cross-sectional area targets such as floating mines...

High Temperature Fiberoptic Thermal Imaging System, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — The proposed Phase 1 program will fabricate and demonstrate a small diameter single fiber endoscope that can perform high temperature thermal imaging in a jet engine...

Satellite Image Time Series Decomposition Based on EEMD

Directory of Open Access Journals (Sweden)

Yun-long Kong

2015-11-01

Full Text Available Satellite Image Time Series (SITS have recently been of great interest due to the emerging remote sensing capabilities for Earth observation. Trend and seasonal components are two crucial elements of SITS. In this paper, a novel framework of SITS decomposition based on Ensemble Empirical Mode Decomposition (EEMD is proposed. EEMD is achieved by sifting an ensemble of adaptive orthogonal components called Intrinsic Mode Functions (IMFs. EEMD is noise-assisted and overcomes the drawback of mode mixing in conventional Empirical Mode Decomposition (EMD. Inspired by these advantages, the aim of this work is to employ EEMD to decompose SITS into IMFs and to choose relevant IMFs for the separation of seasonal and trend components. In a series of simulations, IMFs extracted by EEMD achieved a clear representation with physical meaning. The experimental results of 16-day compositions of Moderate Resolution Imaging Spectroradiometer (MODIS, Normalized Difference Vegetation Index (NDVI, and Global Environment Monitoring Index (GEMI time series with disturbance illustrated the effectiveness and stability of the proposed approach to monitoring tasks, such as applications for the detection of abrupt changes.

Soft x-ray imager (SXI) onboard the NeXT satellite

Science.gov (United States)

Tsuru, Takeshi Go; Takagi, Shin-Ichiro; Matsumoto, Hironori; Inui, Tatsuya; Ozawa, Midori; Koyama, Katsuji; Tsunemi, Hiroshi; Hayashida, Kiyoshi; Miyata, Emi; Ozawa, Hideki; Touhiguchi, Masakuni; Matsuura, Daisuke; Dotani, Tadayasu; Ozaki, Masanobu; Murakami, Hiroshi; Kohmura, Takayoshi; Kitamoto, Shunji; Awaki, Hisamitsu

2006-06-01

We give overview and the current status of the development of the Soft X-ray Imager (SXI) onboard the NeXT satellite. SXI is an X-ray CCD camera placed at the focal plane detector of the Soft X-ray Telescopes for Imaging (SXT-I) onboard NeXT. The pixel size and the format of the CCD is 24 x 24μm (IA) and 2048 x 2048 x 2 (IA+FS). Currently, we have been developing two types of CCD as candidates for SXI, in parallel. The one is front illumination type CCD with moderate thickness of the depletion layer (70 ~ 100μm) as a baseline plan. The other one is the goal plan, in which we develop back illumination type CCD with a thick depletion layer (200 ~ 300μm). For the baseline plan, we successfully developed the proto model 'CCD-NeXT1' with the pixel size of 12μm x 12μm and the CCD size of 24mm x 48mm. The depletion layer of the CCD has reached 75 ~ 85μm. The goal plan is realized by introduction of a new type of CCD 'P-channel CCD', which collects holes in stead of electrons in the common 'N-channel CCD'. By processing a test model of P-channel CCD we have confirmed high quantum efficiency above 10 keV with an equivalent depletion layer of 300μm. A back illumination type of P-channel CCD with a depletion layer of 200μm with aluminum coating for optical blocking has been also successfully developed. We have been also developing a thermo-electric cooler (TEC) with the function of the mechanically support of the CCD wafer without standoff insulators, for the purpose of the reduction of thermal input to the CCD through the standoff insulators. We have been considering the sensor housing and the onboard electronics for the CCD clocking, readout and digital processing of the frame date.

Exploring the use of thermal infrared imaging in human stress research.

Directory of Open Access Journals (Sweden)

Veronika Engert

Full Text Available High resolution thermal infrared imaging is a pioneering method giving indices of sympathetic activity via the contact-free recording of facial tissues (thermal imprints. Compared to established stress markers, the great advantage of this method is its non-invasiveness. The goal of our study was to pilot the use of thermal infrared imaging in the classical setting of human stress research. Thermal imprints were compared to established stress markers (heart rate, heart rate variability, finger temperature, alpha-amylase and cortisol in 15 participants undergoing anticipation, stress and recovery phases of two laboratory stress tests, the Cold Pressor Test and the Trier Social Stress Test. The majority of the thermal imprints proved to be change-sensitive in both tests. While correlations between the thermal imprints and established stress markers were mostly non-significant, the thermal imprints (but not the established stress makers did correlate with stress-induced mood changes. Multivariate pattern analysis revealed that in contrast to the established stress markers the thermal imprints could not disambiguate anticipation, stress and recovery phases of both tests. Overall, these results suggest that thermal infrared imaging is a valuable method for the estimation of sympathetic activity in the stress laboratory setting. The use of this non-invasive method may be particularly beneficial for covert recordings, in the study of special populations showing difficulties in complying with the standard instruments of data collection and in the domain of psychophysiological covariance research. Meanwhile, the established stress markers seem to be superior when it comes to the characterization of complex physiological states during the different phases of the stress cycle.

Differential Spatio-temporal Multiband Satellite Image Clustering using K-means Optimization With Reinforcement Programming

Directory of Open Access Journals (Sweden)

Irene Erlyn Wina Rachmawan

2015-06-01

Full Text Available Deforestration is one of the crucial issues in Indonesia because now Indonesia has world's highest deforestation rate. In other hand, multispectral image delivers a great source of data for studying spatial and temporal changeability of the environmental such as deforestration area. This research present differential image processing methods for detecting nature change of deforestration. Our differential image processing algorithms extract and indicating area automatically. The feature of our proposed idea produce extracted information from multiband satellite image and calculate the area of deforestration by years with calculating data using temporal dataset. Yet, multiband satellite image consists of big data size that were difficult to be handled for segmentation. Commonly, K- Means clustering is considered to be a powerfull clustering algorithm because of its ability to clustering big data. However K-Means has sensitivity of its first generated centroids, which could lead into a bad performance. In this paper we propose a new approach to optimize K-Means clustering using Reinforcement Programming in order to clustering multispectral image. We build a new mechanism for generating initial centroids by implementing exploration and exploitation knowledge from Reinforcement Programming. This optimization will lead a better result for K-means data cluster. We select multispectral image from Landsat 7 in past ten years in Medawai, Borneo, Indonesia, and apply two segmentation areas consist of deforestration land and forest field. We made series of experiments and compared the experimental results of K-means using Reinforcement Programming as optimizing initiate centroid and normal K-means without optimization process. Keywords: Deforestration, Multispectral images, landsat, automatic clustering, K-means.

Simultaneous observation of auroral substorm onset in Polar satellite global images and ground-based all-sky images

Science.gov (United States)

Ieda, Akimasa; Kauristie, Kirsti; Nishimura, Yukitoshi; Miyashita, Yukinaga; Frey, Harald U.; Juusola, Liisa; Whiter, Daniel; Nosé, Masahito; Fillingim, Matthew O.; Honary, Farideh; Rogers, Neil C.; Miyoshi, Yoshizumi; Miura, Tsubasa; Kawashima, Takahiro; Machida, Shinobu

2018-05-01

Substorm onset has originally been defined as a longitudinally extended sudden auroral brightening (Akasofu initial brightening: AIB) followed a few minutes later by an auroral poleward expansion in ground-based all-sky images (ASIs). In contrast, such clearly marked two-stage development has not been evident in satellite-based global images (GIs). Instead, substorm onsets have been identified as localized sudden brightenings that expand immediately poleward. To resolve these differences, optical substorm onset signatures in GIs and ASIs are compared in this study for a substorm that occurred on December 7, 1999. For this substorm, the Polar satellite ultraviolet global imager was operated with a fixed-filter (170 nm) mode, enabling a higher time resolution (37 s) than usual to resolve the possible two-stage development. These data were compared with 20-s resolution green-line (557.7 nm) ASIs at Muonio in Finland. The ASIs revealed the AIB at 2124:50 UT and the subsequent poleward expansion at 2127:50 UT, whereas the GIs revealed only an onset brightening that started at 2127:49 UT. Thus, the onset in the GIs was delayed relative to the AIB and in fact agreed with the poleward expansion in the ASIs. The fact that the AIB was not evident in the GIs may be attributed to the limited spatial resolution of GIs for thin auroral arc brightenings. The implications of these results for the definition of substorm onset are discussed herein.[Figure not available: see fulltext.

A Low-Complexity UEP Methodology Demonstrated on a Turbo-Encoded Wavelet Image Satellite Downlink

Directory of Open Access Journals (Sweden)

Salemi Eric

2008-01-01

Full Text Available Realizing high-quality digital image transmission via a satellite link, while optimizing resource distribution and minimizing battery consumption, is a challenging task. This paper describes a methodology to optimize a turbo-encoded wavelet-based satellite downlink progressive image transmission system with unequal error protection (UEP techniques. To achieve that goal, we instantiate a generic UEP methodology onto the system, and demonstrate that the proposed solution has little impact on the average performance, while greatly reducing the run-time complexity. Based on a simple design-time distortion model and a low-complexity run-time algorithm, the provided solution can dynamically tune the system's configuration to any bitrate constraint or channel condition. The resulting system outperforms in terms of peak signal-to-noise ratio (PSNR, a state-of-the-art, fine-tuned equal error protection (EEP solution by as much as 2 dB.

A Low-Complexity UEP Methodology Demonstrated on a Turbo-Encoded Wavelet Image Satellite Downlink

Directory of Open Access Journals (Sweden)

Eric Salemi

2008-01-01

Full Text Available Realizing high-quality digital image transmission via a satellite link, while optimizing resource distribution and minimizing battery consumption, is a challenging task. This paper describes a methodology to optimize a turbo-encoded wavelet-based satellite downlink progressive image transmission system with unequal error protection (UEP techniques. To achieve that goal, we instantiate a generic UEP methodology onto the system, and demonstrate that the proposed solution has little impact on the average performance, while greatly reducing the run-time complexity. Based on a simple design-time distortion model and a low-complexity run-time algorithm, the provided solution can dynamically tune the system's configuration to any bitrate constraint or channel condition. The resulting system outperforms in terms of peak signal-to-noise ratio (PSNR, a state-of-the-art, fine-tuned equal error protection (EEP solution by as much as 2 dB.

Design Considerations, Modeling and Analysis for the Multispectral Thermal Imager

International Nuclear Information System (INIS)

Borel, C.C.; Clodius, W.B.; Cooke, B.J.; Smith, B.W.; Weber, P.G.

1999-01-01

The design of remote sensing systems is driven by the need to provide cost-effective, substantive answers to questions posed by our customers. This is especially important for space-based systems, which tend to be expensive, and which generally cannot be changed after they are launched. We report here on the approach we employed in developing the desired attributes of a satellite mission, namely the Multispectral Thermal Imager. After an initial scoping study, we applied a procedure which we call: ''End-to-end modeling and analysis (EEM).'' We began with target attributes, translated to observable signatures and then propagated the signatures through the atmosphere to the sensor location. We modeled the sensor attributes to yield a simulated data stream, which was then analyzed to retrieve information about the original target. The retrieved signature was then compared to the original to obtain a figure of merit: hence the term ''end-to-end modeling and analysis.'' We base the EEM in physics to ensure high fidelity and to permit scaling. As the actual design of the payload evolves, and as real hardware is tested, we can update the EEM to facilitate trade studies, and to judge, for example, whether components that deviate from specifications are acceptable

Multitemporal Satellite Images for Knowledge of the Assyrian Capital Cities and for Monitoring Landscape Transformations in the Upper Course of Tigris River

Directory of Open Access Journals (Sweden)

Giuseppe Scardozzi

2011-01-01

Full Text Available The paper is concerned with the contribution that a rich documentation of multitemporal optical satellite images with high resolution provides for the knowledge of the five great Assyrian capital cities (Ashur, Kar-Tukulti-Ninurta, Kalhu, Dur-Sharrukin, and Nineveh, in northern Iraq. These images also allow monitoring changes of landscape in the higher course of the Tigris during the last half century and document damages in archaeological sites during the two Gulf Wars. The data set, available for each city, consists of panchromatic and multispectral images taken between 2001 and 2007 by modern commercial satellites (Ikonos-2, QuickBird-2, and WorldView-1 and of panchromatic photographs of U.S. spy satellites operating between 1965 and 1969 (Corona KH-4B and Gambit KH-7. These photos were taken before diffusion of mechanized agriculture and the expansion of urban areas, so they are very useful to document many archaeological features and the landscape that has been modified in the last decades, as shown by recent satellite images.

Sun glitter imaging analysis of submarine sand waves in HJ-1A/B satellite CCD images

Science.gov (United States)

Zhang, Huaguo; He, Xiekai; Yang, Kang; Fu, Bin; Guan, Weibing

2014-11-01

Submarine sand waves are a widespread bed-form in tidal environment. Submarine sand waves induce current convergence and divergence that affect sea surface roughness thus become visible in sun glitter images. These sun glitter images have been employed for mapping sand wave topography. However, there are lots of effect factors in sun glitter imaging of the submarine sand waves, such as the imaging geometry and dynamic environment condition. In this paper, several sun glitter images from HJ-1A/B in the Taiwan Banks are selected. These satellite sun glitter images are used to discuss sun glitter imaging characteristics in different sensor parameters and dynamic environment condition. To interpret the imaging characteristics, calculating the sun glitter radiance and analyzing its spatial characteristics of the sand wave in different images is the best way. In this study, a simulated model based on sun glitter radiation transmission is adopted to certify the imaging analysis in further. Some results are drawn based on the study. Firstly, the sun glitter radiation is mainly determined by sensor view angle. Second, the current is another key factor for the sun glitter. The opposite current direction will cause exchanging of bright stripes and dark stripes. Third, brightness reversal would happen at the critical angle. Therefore, when using sun glitter image to obtain depth inversion, one is advised to take advantage of image properties of sand waves and to pay attention to key dynamic environment condition and brightness reversal.

Detection of Thermal Erosion Gullies from High-Resolution Images Using Deep Learning

Science.gov (United States)

Huang, L.; Liu, L.; Jiang, L.; Zhang, T.; Sun, Y.

2017-12-01

Thermal erosion gullies, one type of thermokarst landforms, develop due to thawing of ice-rich permafrost. Mapping the location and extent of thermal erosion gullies can help understand the spatial distribution of thermokarst landforms and their temporal evolution. Remote sensing images provide an effective way for mapping thermokarst landforms, especially thermokarst lakes. However, thermal erosion gullies are challenging to map from remote sensing images due to their small sizes and significant variations in geometric/radiometric properties. It is feasible to manually identify these features, as a few previous studies have carried out. However manual methods are labor-intensive, therefore, cannot be used for a large study area. In this work, we conduct automatic mapping of thermal erosion gullies from high-resolution images by using Deep Learning. Our study area is located in Eboling Mountain (Qinghai, China). Within a 6 km2 peatland area underlain by ice-rich permafrost, at least 20 thermal erosional gullies are well developed. The image used is a 15-cm-resolution Digital Orthophoto Map (DOM) generated in July 2016. First, we extracted 14 gully patches and ten non-gully patches as training data. And we performed image augmentation. Next, we fine-tuned the pre-trained model of DeepLab, a deep-learning algorithm for semantic image segmentation based on Deep Convolutional Neural Networks. Then, we performed inference on the whole DOM and obtained intermediate results in forms of polygons for all identified gullies. At last, we removed misidentified polygons based on a few pre-set criteria on the size and shape of each polygon. Our final results include 42 polygons. Validated against field measurements using GPS, most of the gullies are detected correctly. There are 20 false detections due to the small number and low quality of training images. We also found three new gullies that missed in the field observations. This study shows that (1) despite a challenging

Combined Use of Multi-Temporal Optical and Radar Satellite Images for Grassland Monitoring

Directory of Open Access Journals (Sweden)

Pauline Dusseux

2014-06-01

Full Text Available The aim of this study was to assess the ability of optical images, SAR (Synthetic Aperture Radar images and the combination of both types of data to discriminate between grasslands and crops in agricultural areas where cloud cover is very high most of the time, which restricts the use of visible and near-infrared satellite data. We compared the performances of variables extracted from four optical and five SAR satellite images with high/very high spatial resolutions acquired during the growing season. A vegetation index, namely the NDVI (Normalized Difference Vegetation Index, and two biophysical variables, the LAI (Leaf Area Index and the fCOVER (fraction of Vegetation Cover were computed using optical time series and polarization (HH, VV, HV, VH. The polarization ratio and polarimetric decomposition (Freeman–Durden and Cloude–Pottier were calculated using SAR time series. Then, variables derived from optical, SAR and both types of remotely-sensed data were successively classified using the Support Vector Machine (SVM technique. The results show that the classification accuracy of SAR variables is higher than those using optical data (0.98 compared to 0.81. They also highlight that the combination of optical and SAR time series data is of prime interest to discriminate grasslands from crops, allowing an improved classification accuracy.

Satellite Eye for Galathea 3. Annual report 2006

DEFF Research Database (Denmark)

Hasager, Charlotte Bay; Sørensen, Peter; Pedersen, Leif Toudal

The Satellite Eye for Galathea 3 project is collecting satellite images from many satellites and, in particular, from the European ENVISAT satellite along the Galathea 3 global route. The expedition takes place from 11 August 2006 to 27 April 2007. Prior to the expedition several satellite images...... Vædderen, pupils in the classrooms and the public at any moment can take a look at the conditions seen from the eyes of the Earth observing satellites....

Mobile satellite service communications tests using a NASA satellite

Science.gov (United States)

Chambers, Katherine H.; Koschmeder, Louis A.; Hollansworth, James E.; ONeill, Jack; Jones, Robert E.; Gibbons, Richard C.

1995-01-01

Emerging applications of commercial mobile satellite communications include satellite delivery of compact disc (CD) quality radio to car drivers who can select their favorite programming as they drive any distance; transmission of current air traffic data to aircraft; and handheld communication of data and images from any remote corner of the world. Experiments with the enabling technologies and tests and demonstrations of these concepts are being conducted before the first satellite is launched by utilizing an existing NASA spacecraft.

Performance of a thermal neutron radiographic system using imaging plates

International Nuclear Information System (INIS)

Silvani, Maria Ines; Almeida, Gevaldo L. de; Furieri, Rosanne; Lopes, Ricardo T.

2009-01-01

A performance evaluation of a neutron radiographic system equipped with a thermal neutron sensitive imaging plate has been undertaken. It includes the assessment of spatial resolution, linearity, dynamic range and the response to exposure time, as well as a comparison of these parameters with the equivalent ones for neutron radiography employing conventional films and a gadolinium foil as converter. The evaluation and comparison between the radiographic systems have been performed at the Instituto de Engenharia Nuclear - CNEN, using the Argonauta Reactor as source of thermal neutrons and a commercially available imaging plate reader. (author)

kCCA Transformation-Based Radiometric Normalization of Multi-Temporal Satellite Images

Directory of Open Access Journals (Sweden)

Yang Bai

2018-03-01

Full Text Available Radiation normalization is an essential pre-processing step for generating high-quality satellite sequence images. However, most radiometric normalization methods are linear, and they cannot eliminate the regular nonlinear spectral differences. Here we introduce the well-established kernel canonical correlation analysis (kCCA into radiometric normalization for the first time to overcome this problem, which leads to a new kernel method. It can maximally reduce the image differences among multi-temporal images regardless of the imaging conditions and the reflectivity difference. It also perfectly eliminates the impact of nonlinear changes caused by seasonal variation of natural objects. Comparisons with the multivariate alteration detection (CCA-based normalization and the histogram matching, on Gaofen-1 (GF-1 data, indicate that the kCCA-based normalization can preserve more similarity and better correlation between an image-pair and effectively avoid the color error propagation. The proposed method not only builds the common scale or reference to make the radiometric consistency among GF-1 image sequences, but also highlights the interesting spectral changes while eliminates less interesting spectral changes. Our method enables the application of GF-1 data for change detection, land-use, land-cover change detection etc.

Application of SVM on satellite images to detect hotspots in Jharia coal field region of India

Energy Technology Data Exchange (ETDEWEB)

Gautam, R.S.; Singh, D.; Mittal, A.; Sajin, P. [Indian Institute for Technology, Roorkee (India)

2008-07-01

The present paper deals with the application of Support Vector Machine (SVM) and image analysis techniques on NOAA/AVHRR satellite image to detect hotspots on the Jharia coal field region of India. One of the major advantages of using these satellite data is that the data are free with very good temporal resolution; while, one drawback is that these have low spatial resolution (i.e., approximately 1.1 km at nadir). Therefore, it is important to do research by applying some efficient optimization techniques along with the image analysis techniques to rectify these drawbacks and use satellite images for efficient hotspot detection and monitoring. For this purpose, SVM and multi-threshold techniques are explored for hotspot detection. The multi-threshold algorithm is developed to remove the cloud coverage from the land coverage. This algorithm also highlights the hotspots or fire spots in the suspected regions. SVM has the advantage over multi-thresholding technique that it can learn patterns from the examples and therefore is used to optimize the performance by removing the false points which are highlighted in the threshold technique. Both approaches can be used separately or in combination depending on the size of the image. The RBF (Radial Basis Function) kernel is used in training of three sets of inputs: brightness temperature of channel 3, Normalized Difference Vegetation Index (NDVI) and Global Environment Monitoring Index (GEMI), respectively. This makes a classified image in the output that highlights the hotspot and non-hotspot pixels. The performance of the SVM is also compared with the performance obtained from the neural networks and SVM appears to detect hotspots more accurately (greater than 91% classification accuracy) with lesser false alarm rate. The results obtained are found to be in good agreement with the ground based observations of the hotspots.

Diagnosis of the three-phase induction motor using thermal imaging

Science.gov (United States)

Glowacz, Adam; Glowacz, Zygfryd

2017-03-01

Three-phase induction motors are used in the industry commonly for example woodworking machines, blowers, pumps, conveyors, elevators, compressors, mining industry, automotive industry, chemical industry and railway applications. Diagnosis of faults is essential for proper maintenance. Faults may damage a motor and damaged motors generate economic losses caused by breakdowns in production lines. In this paper the authors develop fault diagnostic techniques of the three-phase induction motor. The described techniques are based on the analysis of thermal images of three-phase induction motor. The authors analyse thermal images of 3 states of the three-phase induction motor: healthy three-phase induction motor, three-phase induction motor with 2 broken bars, three-phase induction motor with faulty ring of squirrel-cage. In this paper the authors develop an original method of the feature extraction of thermal images MoASoID (Method of Areas Selection of Image Differences). This method compares many training sets together and it selects the areas with the biggest changes for the recognition process. Feature vectors are obtained with the use of mentioned MoASoID and image histogram. Next 3 methods of classification are used: NN (the Nearest Neighbour classifier), K-means, BNN (the back-propagation neural network). The described fault diagnostic techniques are useful for protection of three-phase induction motor and other types of rotating electrical motors such as: DC motors, generators, synchronous motors.

A Study on infrared tracing and monitoring of thermal discharge from the power plants

Energy Technology Data Exchange (ETDEWEB)

Choi, Byung Sun; Hong, Wuk Hee; Kim, Yung Bae; Park, Jang Rae; Choi, Yung An; Park, Yung San [Korea Electric Power Corp. (KEPCO), Taejon (Korea, Republic of). Research Center

1996-08-01

Massive discharge of cooling water from the nuclear power plants as well as many thermal power plants would cause serious environmental problems. Hence, the task of predicting cooling water dispersion areas has enormous importance for better environmental management related with the power plant operation. For the last two decades, extensive field survey and dispersion modeling have been mainly applied to predict thermal discharge dispersion areas. In this study, the method of infrared thermal sensing was tested as a possible means of measuring the affected areas of thermal discharge at the thermal power plant sites. Many IR images obtained by using the terrestrial camera, or by using the airborne scanner, or from the Landsat iv satellite were analyzed from the pc with the IDRISI and resource software and further enhanced with other image analysis technologies. The result of study proved this IR imaging technology to be an potentially cost-effective tool for assessment of water-temperature increase caused by the thermal discharge from the power plants, however, further elaboration of procedure was highly requested. (author). 9 refs., 24 figs.

Automatic detection of diseased tomato plants using thermal and stereo visible light images.

Directory of Open Access Journals (Sweden)

Shan-e-Ahmed Raza

Full Text Available Accurate and timely detection of plant diseases can help mitigate the worldwide losses experienced by the horticulture and agriculture industries each year. Thermal imaging provides a fast and non-destructive way of scanning plants for diseased regions and has been used by various researchers to study the effect of disease on the thermal profile of a plant. However, thermal image of a plant affected by disease has been known to be affected by environmental conditions which include leaf angles and depth of the canopy areas accessible to the thermal imaging camera. In this paper, we combine thermal and visible light image data with depth information and develop a machine learning system to remotely detect plants infected with the tomato powdery mildew fungus Oidium neolycopersici. We extract a novel feature set from the image data using local and global statistics and show that by combining these with the depth information, we can considerably improve the accuracy of detection of the diseased plants. In addition, we show that our novel feature set is capable of identifying plants which were not originally inoculated with the fungus at the start of the experiment but which subsequently developed disease through natural transmission.

Hot Shoes in the Room: Authentication of Thermal Imaging for Quantitative Forensic Analysis

Directory of Open Access Journals (Sweden)

Justin H. J. Chua

2018-01-01

Full Text Available Thermal imaging has been a mainstay of military applications and diagnostic engineering. However, there is currently no formalised procedure for the use of thermal imaging capable of standing up to judicial scrutiny. Using a scientifically sound characterisation method, we describe the cooling function of three common shoe types at an ambient room temperature of 22 °C (295 K based on the digital output of a consumer-grade FLIR i50 thermal imager. Our method allows the reliable estimation of cooling time from pixel intensity values within a time interval of 3 to 25 min after shoes have been removed. We found a significant linear relationship between pixel intensity level and temperature. The calibration method allows the replicable determination of independent thermal cooling profiles for objects without the need for emissivity values associated with non-ideal black-body thermal radiation or system noise functions. The method has potential applications for law enforcement and forensic research, such as cross-validating statements about time spent by a person in a room. The use of thermal images can thus provide forensic scientists, law enforcement officials, and legislative bodies with an efficient and cost-effective tool for obtaining and interpreting time-based evidence.

USING OF THE MULTITEMPORAL THERMAL INFRARED SATELLITE IMAGERY FOR NATURAL AREAS MAPPING (CASE OF MENDELEEV VOLCANO

Directory of Open Access Journals (Sweden)

M. Y. Grishchenko

2014-01-01

Full Text Available In the paper authors examine the mountain group of Mendeleev volcano situated on the Kunashir island, Kuril archipelago, Russia. Ground observations were led to examine the vegetation cover of the area as well as its typical landscapes. The other type of used data is Landsat imagery. Images were combined into multitemporal thermal infrared and multispectral pictures, which were classified to reveal the heterogeneity of the study area. Ground observations and comparison of the classification results with landscape map derive that the multitemporal thermal infrared image classification result describes better the vegetation cover structure of the area and particularity of its typical landscapes distribution. It leads to the proposition that miltitemporal thermal infrared imagery can be used to refine landscape and vegetation cover contours. 

Rule-based land cover classification from very high-resolution satellite image with multiresolution segmentation

Science.gov (United States)

Haque, Md. Enamul; Al-Ramadan, Baqer; Johnson, Brian A.

2016-07-01

Multiresolution segmentation and rule-based classification techniques are used to classify objects from very high-resolution satellite images of urban areas. Custom rules are developed using different spectral, geometric, and textural features with five scale parameters, which exploit varying classification accuracy. Principal component analysis is used to select the most important features out of a total of 207 different features. In particular, seven different object types are considered for classification. The overall classification accuracy achieved for the rule-based method is 95.55% and 98.95% for seven and five classes, respectively. Other classifiers that are not using rules perform at 84.17% and 97.3% accuracy for seven and five classes, respectively. The results exploit coarse segmentation for higher scale parameter and fine segmentation for lower scale parameter. The major contribution of this research is the development of rule sets and the identification of major features for satellite image classification where the rule sets are transferable and the parameters are tunable for different types of imagery. Additionally, the individual objectwise classification and principal component analysis help to identify the required object from an arbitrary number of objects within images given ground truth data for the training.

Detecting thermal phase transitions in corneal stroma by fluorescence micro-imaging analysis

Science.gov (United States)

Matteini, P.; Rossi, F.; Ratto, F.; Bruno, I.; Nesi, P.; Pini, R.

2008-02-01

Thermal modifications induced in corneal stroma were investigated by the use of fluorescence microscopy. Freshly extracted porcine corneas were immersed for 5 minutes in a water bath at temperatures in the 35-90°C range and stored in formalin. The samples were then sliced in 200-μm-thick transversal sections and analyzed under a stereomicroscope to assess corneal shrinkage. Fluorescence images of the thermally treated corneal samples were acquired using a slow-scan cooled CCD camera, after staining the slices with Indocyanine Green (ICG) fluorescent dye which allowed to detect fluorescence signal from the whole tissue. All measurements were performed using an inverted epifluorescence microscope equipped with a mercury lamp. The thermally-induced modifications to the corneal specimens were evaluated by studying the grey level distribution in the fluorescence images. For each acquired image, Discrete Fourier Transform (DFT) and entropy analyses were performed. The spatial distribution of DFT absolute value indicated the spatial orientation of the lamellar planes, while entropy was used to study the image texture, correlated to the stromal structural transitions. As a result, it was possible to indicate a temperature threshold value (62°C) for high thermal damage, resulting in a disorganization of the lamellar planes and in full agreement with the measured temperature for corneal shrinkage onset. Analysis of the image entropy evidenced five strong modifications in stromal architecture at temperatures of ~45°C, 53°C, 57°C, 66°C, 75°C. The proposed procedure proved to be an effective micro-imaging method capable of detecting subtle changes in corneal tissue subjected to thermal treatment.

Cyclone track forecasting based on satellite images using artificial neural networks

OpenAIRE

Kovordanyi, Rita; Roy, Chandan

2009-01-01

Many places around the world are exposed to tropical cyclones and associated storm surges. In spite of massive efforts, a great number of people die each year as a result of cyclone events. To mitigate this damage, improved forecasting techniques must be developed. The technique presented here uses artificial neural networks to interpret NOAA-AVHRR satellite images. A multi-layer neural network, resembling the human visual system, was trained to forecast the movement of cyclones based on sate...

Remotely monitoring evaporation rate and soil water status using thermal imaging and "three-temperatures model (3T Model)" under field-scale conditions.

Science.gov (United States)

Qiu, Guo Yu; Zhao, Ming

2010-03-01

Remote monitoring of soil evaporation and soil water status is necessary for water resource and environment management. Ground based remote sensing can be the bridge between satellite remote sensing and ground-based point measurement. The primary object of this study is to provide an algorithm to estimate evaporation and soil water status by remote sensing and to verify its accuracy. Observations were carried out in a flat field with varied soil water content. High-resolution thermal images were taken with a thermal camera; soil evaporation was measured with a weighing lysimeter; weather data were recorded at a nearby meteorological station. Based on the thermal imaging and the three-temperatures model (3T model), we developed an algorithm to estimate soil evaporation and soil water status. The required parameters of the proposed method were soil surface temperature, air temperature, and solar radiation. By using the proposed method, daily variation in soil evaporation was estimated. Meanwhile, soil water status was remotely monitored by using the soil evaporation transfer coefficient. Results showed that the daily variation trends of measured and estimated evaporation agreed with each other, with a regression line of y = 0.92x and coefficient of determination R(2) = 0.69. The simplicity of the proposed method makes the 3T model a potentially valuable tool for remote sensing.

Thermal design, analysis and comparison on three concepts of space solar power satellite

Science.gov (United States)

Yang, Chen; Hou, Xinbin; Wang, Li

2017-08-01

Space solar power satellites (SSPS) have been widely studied as systems for collecting solar energy in space and transmitting it wirelessly to earth. A previously designed planar SSPS concept collects solar power in two huge arrays and then transmits it through one side of the power-conduction joint to the antenna. However, the system's one group of power-conduction joints may induce a single point of failure. As an SSPS concept, the module symmetrical concentrator (MSC) architecture has many advantages. This architecture can help avoid the need for a large, potentially failure-prone conductive rotating joint and limit wiring mass. However, the thermal control system has severely restricted the rapid development of MSC, especially in the sandwich module. Because of the synchronous existence of five suns concentration and solar external heat flux, the sandwich module will have a very high temperature, which will surpass the permissible temperature of the solar cells. Recently, an alternate multi-rotary joints (MR) SSPS concept was designed by the China Academy of Space Technology (CAST). This system has multiple joints to avoid the problem of a single point of failure. Meanwhile, this concept has another advantage for reducing the high power and heat removal in joints. It is well known to us that, because of the huge external flux in SSPS, the thermal management sub-system is an important component that cannot be neglected. Based on the three SSPS concepts, this study investigated the thermal design and analysis of a 1-km, gigawatt-level transmitting antenna in SSPS. This study compares the thermal management sub-systems of power-conduction joints in planar and MR SSPS. Moreover, the study considers three classic thermal control architectures of the MSC's sandwich module: tile, step, and separation. The study also presents an elaborate parameter design, analysis and discussion of step architecture. Finally, the results show the thermal characteristics of each SSPS

Object-Oriented Analysis of Satellite Images Using Artificial Neural Networks for Post-Earthquake Buildings Change Detection

Science.gov (United States)

Khodaverdi zahraee, N.; Rastiveis, H.

2017-09-01

Earthquake is one of the most divesting natural events that threaten human life during history. After the earthquake, having information about the damaged area, the amount and type of damage can be a great help in the relief and reconstruction for disaster managers. It is very important that these measures should be taken immediately after the earthquake because any negligence could be more criminal losses. The purpose of this paper is to propose and implement an automatic approach for mapping destructed buildings after an earthquake using pre- and post-event high resolution satellite images. In the proposed method after preprocessing, segmentation of both images is performed using multi-resolution segmentation technique. Then, the segmentation results are intersected with ArcGIS to obtain equal image objects on both images. After that, appropriate textural features, which make a better difference between changed or unchanged areas, are calculated for all the image objects. Finally, subtracting the extracted textural features from pre- and post-event images, obtained values are applied as an input feature vector in an artificial neural network for classifying the area into two classes of changed and unchanged areas. The proposed method was evaluated using WorldView2 satellite images, acquired before and after the 2010 Haiti earthquake. The reported overall accuracy of 93% proved the ability of the proposed method for post-earthquake buildings change detection.

Tile-Level Annotation of Satellite Images Using Multi-Level Max-Margin Discriminative Random Field

Directory of Open Access Journals (Sweden)

Hong Sun

2013-05-01

Full Text Available This paper proposes a multi-level max-margin discriminative analysis (M3DA framework, which takes both coarse and fine semantics into consideration, for the annotation of high-resolution satellite images. In order to generate more discriminative topic-level features, the M3DA uses the maximum entropy discrimination latent Dirichlet Allocation (MedLDA model. Moreover, for improving the spatial coherence of visual words neglected by M3DA, conditional random field (CRF is employed to optimize the soft label field composed of multiple label posteriors. The framework of M3DA enables one to combine word-level features (generated by support vector machines and topic-level features (generated by MedLDA via the bag-of-words representation. The experimental results on high-resolution satellite images have demonstrated that, using the proposed method can not only obtain suitable semantic interpretation, but also improve the annotation performance by taking into account the multi-level semantics and the contextual information.

Improving Sediment Transport Prediction by Assimilating Satellite Images in a Tidal Bay Model of Hong Kong

Directory of Open Access Journals (Sweden)

Peng Zhang

2014-03-01

Full Text Available Numerical models being one of the major tools for sediment dynamic studies in complex coastal waters are now benefitting from remote sensing images that are easily available for model inputs. The present study explored various methods of integrating remote sensing ocean color data into a numerical model to improve sediment transport prediction in a tide-dominated bay in Hong Kong, Deep Bay. Two sea surface sediment datasets delineated from satellite images from the Moderate Resolution Imaging Spectra-radiometer (MODIS were assimilated into a coastal ocean model of the bay for one tidal cycle. It was found that remote sensing sediment information enhanced the sediment transport model ability by validating the model results with in situ measurements. Model results showed that root mean square errors of forecast sediment both at the surface layer and the vertical layers from the model with satellite sediment assimilation are reduced by at least 36% over the model without assimilation.

Road Network Extraction from VHR Satellite Images Using Context Aware Object Feature Integration and Tensor Voting

Directory of Open Access Journals (Sweden)

Mehdi Maboudi

2016-08-01

Full Text Available Road networks are very important features in geospatial databases. Even though high-resolution optical satellite images have already been acquired for more than a decade, tools for automated extraction of road networks from these images are still rare. One consequence of this is the need for manual interaction which, in turn, is time and cost intensive. In this paper, a multi-stage approach is proposed which integrates structural, spectral, textural, as well as contextual information of objects to extract road networks from very high resolution satellite images. Highlights of the approach are a novel linearity index employed for the discrimination of elongated road segments from other objects and customized tensor voting which is utilized to fill missing parts of the network. Experiments are carried out with different datasets. Comparison of the achieved results with the results of seven state-of-the-art methods demonstrated the efficiency of the proposed approach.

The Calipso Thermal Control Subsystem

Science.gov (United States)

Gasbarre, Joseph F.; Ousley, Wes; Valentini, Marc; Thomas, Jason; Dejoie, Joel

2007-01-01

The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) is a joint NASA-CNES mission to study the Earth s cloud and aerosol layers. The satellite is composed of a primary payload (built by Ball Aerospace) and a spacecraft platform bus (PROTEUS, built by Alcatel Alenia Space). The thermal control subsystem (TCS) for the CALIPSO satellite is a passive design utilizing radiators, multi-layer insulation (MLI) blankets, and both operational and survival surface heaters. The most temperature sensitive component within the satellite is the laser system. During thermal vacuum testing of the integrated satellite, the laser system s operational heaters were found to be inadequate in maintaining the lasers required set point. In response, a solution utilizing the laser system s survival heaters to augment the operational heaters was developed with collaboration between NASA, CNES, Ball Aerospace, and Alcatel-Alenia. The CALIPSO satellite launched from Vandenberg Air Force Base in California on April 26th, 2006. Evaluation of both the platform and payload thermal control systems show they are performing as expected and maintaining the critical elements of the satellite within acceptable limits.

Human emotions detection based on a smart-thermal system of thermographic images

Science.gov (United States)

Cruz-Albarran, Irving A.; Benitez-Rangel, Juan P.; Osornio-Rios, Roque A.; Morales-Hernandez, Luis A.

2017-03-01

This work presents a noninvasive methodology to obtain biomedical thermal imaging which provide relevant information that may assist in the diagnosis of emotions. Biomedical thermal images of the facial expressions of 44 subjects were captured experiencing joy, disgust, anger, fear and sadness. The analysis of these thermograms was carried out through its thermal value not with its intensity value. Regions of interest were obtained through image processing techniques that allow to differentiate between the subject and the background, having only the subject, the centers of each region of interest were obtained in order to get the same region of the face for each subject. Through the thermal analysis a biomarker for each region of interest was obtained, these biomarkers can diagnose when an emotion takes place. Because each subject tends to react differently to the same stimuli, a self-calibration phase is proposed, its function is to have the same thermal trend for each subject in order to make a decision so that the five emotions can be correctly diagnosed through a top-down hierarchical classifier. As a final result, a smart-thermal system that diagnose emotions was obtained and it was tested on twenty-five subjects (625 thermograms). The results of this test were 89.9% successful.

Segmentation techniques for extracting humans from thermal images

CSIR Research Space (South Africa)

Dickens, JS

2011-11-01

Full Text Available A pedestrian detection system for underground mine vehicles is being developed that requires the segmentation of people from thermal images in underground mine tunnels. A number of thresholding techniques are outlined and their performance on a...

Sediment plume model-a comparison between use of measured turbidity data and satellite images for model calibration.

Science.gov (United States)

Sadeghian, Amir; Hudson, Jeff; Wheater, Howard; Lindenschmidt, Karl-Erich

2017-08-01

In this study, we built a two-dimensional sediment transport model of Lake Diefenbaker, Saskatchewan, Canada. It was calibrated by using measured turbidity data from stations along the reservoir and satellite images based on a flood event in 2013. In June 2013, there was heavy rainfall for two consecutive days on the frozen and snow-covered ground in the higher elevations of western Alberta, Canada. The runoff from the rainfall and the melted snow caused one of the largest recorded inflows to the headwaters of the South Saskatchewan River and Lake Diefenbaker downstream. An estimated discharge peak of over 5200 m 3 /s arrived at the reservoir inlet with a thick sediment front within a few days. The sediment plume moved quickly through the entire reservoir and remained visible from satellite images for over 2 weeks along most of the reservoir, leading to concerns regarding water quality. The aims of this study are to compare, quantitatively and qualitatively, the efficacy of using turbidity data and satellite images for sediment transport model calibration and to determine how accurately a sediment transport model can simulate sediment transport based on each of them. Both turbidity data and satellite images were very useful for calibrating the sediment transport model quantitatively and qualitatively. Model predictions and turbidity measurements show that the flood water and suspended sediments entered upstream fairly well mixed and moved downstream as overflow with a sharp gradient at the plume front. The model results suggest that the settling and resuspension rates of sediment are directly proportional to flow characteristics and that the use of constant coefficients leads to model underestimation or overestimation unless more data on sediment formation become available. Hence, this study reiterates the significance of the availability of data on sediment distribution and characteristics for building a robust and reliable sediment transport model.

Space situational awareness satellites and ground based radiation counting and imaging detector technology

International Nuclear Information System (INIS)

Jansen, Frank; Behrens, Joerg; Pospisil, Stanislav; Kudela, Karel

2011-01-01

We review the current status from the scientific and technological point of view of solar energetic particles, solar and galactic cosmic ray measurements as well as high energy UV-, X- and gamma-ray imaging of the Sun. These particles and electromagnetic data are an important tool for space situational awareness (SSA) aspects like space weather storm predictions to avoid failures in space, air and ground based technological systems. Real time data acquisition, position and energy sensitive imaging are demanded by the international space weather forecast services. We present how newly developed, highly miniaturized radiation detectors can find application in space in view of future SSA related satellites as a novel space application due to their counting and imaging capabilities.

Space situational awareness satellites and ground based radiation counting and imaging detector technology

Energy Technology Data Exchange (ETDEWEB)

Jansen, Frank, E-mail: frank.jansen@dlr.de [DLR Institute of Space Systems, Robert-Hooke-Str. 7, 28359 Bremen (Germany); Behrens, Joerg [DLR Institute of Space Systems, Robert-Hooke-Str. 7, 28359 Bremen (Germany); Pospisil, Stanislav [Czech Technical University, IEAP, 12800 Prague 2, Horska 3a/22 (Czech Republic); Kudela, Karel [Slovak Academy of Sciences, IEP, 04001 Kosice, Watsonova 47 (Slovakia)

2011-05-15

We review the current status from the scientific and technological point of view of solar energetic particles, solar and galactic cosmic ray measurements as well as high energy UV-, X- and gamma-ray imaging of the Sun. These particles and electromagnetic data are an important tool for space situational awareness (SSA) aspects like space weather storm predictions to avoid failures in space, air and ground based technological systems. Real time data acquisition, position and energy sensitive imaging are demanded by the international space weather forecast services. We present how newly developed, highly miniaturized radiation detectors can find application in space in view of future SSA related satellites as a novel space application due to their counting and imaging capabilities.

Collage of Saturn's smaller satellites

Science.gov (United States)

1981-01-01

This family portrait shows the smaller satellites of Saturn as viewed by Voyager 2 during its swing through the Saturnian system. The following chart corresponds to this composite photograph (distance from the planet increases from left to right) and lists names, standard numerical designations and approximate dimensions (radii where indicated) in kilometers: 1980S26Outer F-ringshepherd120 X 100 1980S1Leadingco-orbital220 X 160 1980S25TrailingTethys trojanradii: 25 1980S28Outer Ashepherdradii: 20 1980S27Inner F-ringco-orbital145 X 70 1980S3TrailingTethys trojan140 X 100 1980S13LeadingTethys trojanradii: 30 1980S6LeadingDione trojanradii: 30 These images have been scaled to show the satellites in true relative sizes. This set of small objects ranges in size from small asteroidal scales to nearly the size of Saturn's moon Mimas. They are probably fragments of somewhat larger bodies broken up during the bombardment period that followed accretion of the Saturnian system. Scientists believe they may be mostly icy bodies with a mixture of meteorite rock. They are somewhat less reflective than the larger satellites, suggesting that thermal evolution of the larger moons 'cleaned up' their icy surfaces. The Voyager project is managed for NASA by the Jet Propulsion Laboratory, Pasadena, Calif.

The analysis and rationale behind the upgrading of existing standard definition thermal imagers to high definition

Science.gov (United States)

Goss, Tristan M.

2016-05-01

With 640x512 pixel format IR detector arrays having been on the market for the past decade, Standard Definition (SD) thermal imaging sensors have been developed and deployed across the world. Now with 1280x1024 pixel format IR detector arrays becoming readily available designers of thermal imager systems face new challenges as pixel sizes reduce and the demand and applications for High Definition (HD) thermal imaging sensors increases. In many instances the upgrading of existing under-sampled SD thermal imaging sensors into more optimally sampled or oversampled HD thermal imaging sensors provides a more cost effective and reduced time to market option than to design and develop a completely new sensor. This paper presents the analysis and rationale behind the selection of the best suited HD pixel format MWIR detector for the upgrade of an existing SD thermal imaging sensor to a higher performing HD thermal imaging sensor. Several commercially available and "soon to be" commercially available HD small pixel IR detector options are included as part of the analysis and are considered for this upgrade. The impact the proposed detectors have on the sensor's overall sensitivity, noise and resolution is analyzed, and the improved range performance is predicted. Furthermore with reduced dark currents due to the smaller pixel sizes, the candidate HD MWIR detectors are operated at higher temperatures when compared to their SD predecessors. Therefore, as an additional constraint and as a design goal, the feasibility of achieving upgraded performance without any increase in the size, weight and power consumption of the thermal imager is discussed herein.

Backthinned TDI CCD image sensor design and performance for the Pleiades high resolution Earth observation satellites

Science.gov (United States)

Materne, A.; Bardoux, A.; Geoffray, H.; Tournier, T.; Kubik, P.; Morris, D.; Wallace, I.; Renard, C.

2017-11-01

The PLEIADES-HR Earth observing satellites, under CNES development, combine a 0.7m resolution panchromatic channel, and a multispectral channel allowing a 2.8 m resolution, in 4 spectral bands. The 2 satellites will be placed on a sun-synchronous orbit at an altitude of 695 km. The camera operates in push broom mode, providing images across a 20 km swath. This paper focuses on the specifications, design and performance of the TDI detectors developed by e2v technologies under CNES contract for the panchromatic channel. Design drivers, derived from the mission and satellite requirements, architecture of the sensor and measurement results for key performances of the first prototypes are presented.

The CALIPSO Integrated Thermal Control Subsystem

Science.gov (United States)

Gasbarre, Joseph F.; Ousley, Wes; Valentini, Marc; Thomas, Jason; Dejoie, Joel

2007-01-01

The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) is a joint NASA-CNES mission to study the Earth's cloud and aerosol layers. The satellite is composed of a primary payload (built by Ball Aerospace) and a spacecraft platform bus (PROTEUS, built by Alcatel Alenia Space). The thermal control subsystem (TCS) for the CALIPSO satellite is a passive design utilizing radiators, multi-layer insulation (MLI) blankets, and both operational and survival surface heaters. The most temperature sensitive component within the satellite is the laser system. During thermal vacuum testing of the integrated satellite, the laser system's operational heaters were found to be inadequate in maintaining the lasers required set point. In response, a solution utilizing the laser system's survival heaters to augment the operational heaters was developed with collaboration between NASA, CNES, Ball Aerospace, and Alcatel-Alenia. The CALIPSO satellite launched from Vandenberg Air Force Base in California on April 26th, 2006. Evaluation of both the platform and payload thermal control systems show they are performing as expected and maintaining the critical elements of the satellite within acceptable limits.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Aynak mineral district in Afghanistan: Chapter E in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Aynak mineral district, which has copper deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA,2008,2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kundalyan mineral district in Afghanistan: Chapter H in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Kundalyan mineral district, which has porphyry copper and gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Herat mineral district in Afghanistan: Chapter T in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Herat mineral district, which has barium and limestone deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Badakhshan mineral district in Afghanistan: Chapter F in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Badakhshan mineral district, which has gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA,2007,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products

Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This DS consists of the locally enhanced ALOS image mosaics for each of the 24 mineral project areas (referred to herein as areas of interest), whose locality names, locations, and main mineral occurrences are shown on the index map of Afghanistan (fig. 1). ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency, but the image processing has altered the original pixel structure and all image values of the JAXA

Infrared thermal imaging for automated detection of diabetic foot complications

NARCIS (Netherlands)

van Netten, Jaap J.; van Baal, Jeff G.; Liu, C.; van der Heijden, Ferdinand; Bus, Sicco A.

Background: Although thermal imaging can be a valuable technology in the prevention and management of diabetic foot disease, it is not yet widely used in clinical practice. Technological advancement in infrared imaging increases its application range. The aim was to explore the first steps in the

Infrared thermal imaging for automated detection of diabetic foot complications

NARCIS (Netherlands)

van Netten, Jaap J.; van Baal, Jeff G.; Liu, Chanjuan; van der Heijden, Ferdi; Bus, Sicco A.

2013-01-01

Although thermal imaging can be a valuable technology in the prevention and management of diabetic foot disease, it is not yet widely used in clinical practice. Technological advancement in infrared imaging increases its application range. The aim was to explore the first steps in the applicability

Inexpensive land-use maps extracted from satellite data

Science.gov (United States)

Barney, T. W.; Barr, D. J.; Elifrits, C. D.; Johannsen, C. J.

1979-01-01

Satellite images are interpretable with minimal skill and equipment by employing method which uses false color composite print of image of area transmitted from Landsat satellite. Method is effective for those who have little experience with satellite imagery, little time, and little money available.

Teaching physics and understanding infrared thermal imaging

Science.gov (United States)

Vollmer, Michael; Möllmann, Klaus-Peter

2017-08-01

Infrared thermal imaging is a very rapidly evolving field. The latest trends are small smartphone IR camera accessories, making infrared imaging a widespread and well-known consumer product. Applications range from medical diagnosis methods via building inspections and industrial predictive maintenance etc. also to visualization in the natural sciences. Infrared cameras do allow qualitative imaging and visualization but also quantitative measurements of the surface temperatures of objects. On the one hand, they are a particularly suitable tool to teach optics and radiation physics and many selected topics in different fields of physics, on the other hand there is an increasing need of engineers and physicists who understand these complex state of the art photonics systems. Therefore students must also learn and understand the physics underlying these systems.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kunduz mineral district in Afghanistan: Chapter S in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Kunduz mineral district, which has celestite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Dudkash mineral district in Afghanistan: Chapter R in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Dudkash mineral district, which has industrial mineral deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Tourmaline mineral district in Afghanistan: Chapter J in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Tourmaline mineral district, which has tin deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products

Effects of satellite image spatial aggregation and resolution on estimates of forest land area

Science.gov (United States)

M.D. Nelson; R.E. McRoberts; G.R. Holden; M.E. Bauer

2009-01-01

Satellite imagery is being used increasingly in association with national forest inventories (NFIs) to produce maps and enhance estimates of forest attributes. We simulated several image spatial resolutions within sparsely and heavily forested study areas to assess resolution effects on estimates of forest land area, independent of other sensor characteristics. We...

Simultaneous measurement of thermal conductivity and heat capacity by flash thermal imaging methods

Science.gov (United States)

Tao, N.; Li, X. L.; Sun, J. G.

2017-06-01

Thermal properties are important for material applications involved with temperature. Although many measurement methods are available, they may not be convenient to use or have not been demonstrated suitable for testing of a wide range of materials. To address this issue, we developed a new method for the nondestructive measurement of the thermal effusivity of bulk materials with uniform property. This method is based on the pulsed thermal imaging-multilayer analysis (PTI-MLA) method that has been commonly used for testing of coating materials. Because the test sample for PTI-MLA has to be in a two-layer configuration, we have found a commonly used commercial tape to construct such test samples with the tape as the first-layer material and the bulk material as the substrate. This method was evaluated for testing of six selected solid materials with a wide range of thermal properties covering most engineering materials. To determine both thermal conductivity and heat capacity, we also measured the thermal diffusivity of these six materials by the well-established flash method using the same experimental instruments with a different system setup. This paper provides a description of these methods, presents detailed experimental tests and data analyses, and discusses measurement results and their comparison with literature values.

An intelligent approach for cooling radiator fault diagnosis based on infrared thermal image processing technique

International Nuclear Information System (INIS)

Taheri-Garavand, Amin; Ahmadi, Hojjat; Omid, Mahmoud; Mohtasebi, Seyed Saeid; Mollazade, Kaveh; Russell Smith, Alan John; Carlomagno, Giovanni Maria

2015-01-01

This research presents a new intelligent fault diagnosis and condition monitoring system for classification of different conditions of cooling radiator using infrared thermal images. The system was adopted to classify six types of cooling radiator faults; radiator tubes blockage, radiator fins blockage, loose connection between fins and tubes, radiator door failure, coolant leakage, and normal conditions. The proposed system consists of several distinct procedures including thermal image acquisition, image pre-processing, image processing, two-dimensional discrete wavelet transform (2D-DWT), feature extraction, feature selection using a genetic algorithm (GA), and finally classification by artificial neural networks (ANNs). The 2D-DWT is implemented to decompose the thermal images. Subsequently, statistical texture features are extracted from the original images and are decomposed into thermal images. The significant selected features are used to enhance the performance of the designed ANN classifier for the 6 types of cooling radiator conditions (output layer) in the next stage. For the tested system, the input layer consisted of 16 neurons based on the feature selection operation. The best performance of ANN was obtained with a 16-6-6 topology. The classification results demonstrated that this system can be employed satisfactorily as an intelligent condition monitoring and fault diagnosis for a class of cooling radiator. - Highlights: • Intelligent fault diagnosis of cooling radiator using thermal image processing. • Thermal image processing in a multiscale representation structure by 2D-DWT. • Selection features based on a hybrid system that uses both GA and ANN. • Application of ANN as classifier. • Classification accuracy of fault detection up to 93.83%

Post launch calibration and testing of the Advanced Baseline Imager on the GOES-R satellite

Science.gov (United States)

Lebair, William; Rollins, C.; Kline, John; Todirita, M.; Kronenwetter, J.

2016-05-01

The Geostationary Operational Environmental Satellite R (GOES-R) series is the planned next generation of operational weather satellites for the United State's National Oceanic and Atmospheric Administration. The first launch of the GOES-R series is planned for October 2016. The GOES-R series satellites and instruments are being developed by the National Aeronautics and Space Administration (NASA). One of the key instruments on the GOES-R series is the Advance Baseline Imager (ABI). The ABI is a multi-channel, visible through infrared, passive imaging radiometer. The ABI will provide moderate spatial and spectral resolution at high temporal and radiometric resolution to accurately monitor rapidly changing weather. Initial on-orbit calibration and performance characterization is crucial to establishing baseline used to maintain performance throughout mission life. A series of tests has been planned to establish the post launch performance and establish the parameters needed to process the data in the Ground Processing Algorithm. The large number of detectors for each channel required to provide the needed temporal coverage presents unique challenges for accurately calibrating ABI and minimizing striping. This paper discusses the planned tests to be performed on ABI over the six-month Post Launch Test period and the expected performance as it relates to ground tests.

Heuristic Scheduling Algorithm Oriented Dynamic Tasks for Imaging Satellites

Directory of Open Access Journals (Sweden)

Maocai Wang

2014-01-01

Full Text Available Imaging satellite scheduling is an NP-hard problem with many complex constraints. This paper researches the scheduling problem for dynamic tasks oriented to some emergency cases. After the dynamic properties of satellite scheduling were analyzed, the optimization model is proposed in this paper. Based on the model, two heuristic algorithms are proposed to solve the problem. The first heuristic algorithm arranges new tasks by inserting or deleting them, then inserting them repeatedly according to the priority from low to high, which is named IDI algorithm. The second one called ISDR adopts four steps: insert directly, insert by shifting, insert by deleting, and reinsert the tasks deleted. Moreover, two heuristic factors, congestion degree of a time window and the overlapping degree of a task, are employed to improve the algorithm’s performance. Finally, a case is given to test the algorithms. The results show that the IDI algorithm is better than ISDR from the running time point of view while ISDR algorithm with heuristic factors is more effective with regard to algorithm performance. Moreover, the results also show that our method has good performance for the larger size of the dynamic tasks in comparison with the other two methods.

Integrating multisensor satellite data merging and image reconstruction in support of machine learning for better water quality management.

Science.gov (United States)

Chang, Ni-Bin; Bai, Kaixu; Chen, Chi-Farn

2017-10-01

Monitoring water quality changes in lakes, reservoirs, estuaries, and coastal waters is critical in response to the needs for sustainable development. This study develops a remote sensing-based multiscale modeling system by integrating multi-sensor satellite data merging and image reconstruction algorithms in support of feature extraction with machine learning leading to automate continuous water quality monitoring in environmentally sensitive regions. This new Earth observation platform, termed "cross-mission data merging and image reconstruction with machine learning" (CDMIM), is capable of merging multiple satellite imageries to provide daily water quality monitoring through a series of image processing, enhancement, reconstruction, and data mining/machine learning techniques. Two existing key algorithms, including Spectral Information Adaptation and Synthesis Scheme (SIASS) and SMart Information Reconstruction (SMIR), are highlighted to support feature extraction and content-based mapping. Whereas SIASS can support various data merging efforts to merge images collected from cross-mission satellite sensors, SMIR can overcome data gaps by reconstructing the information of value-missing pixels due to impacts such as cloud obstruction. Practical implementation of CDMIM was assessed by predicting the water quality over seasons in terms of the concentrations of nutrients and chlorophyll-a, as well as water clarity in Lake Nicaragua, providing synergistic efforts to better monitor the aquatic environment and offer insightful lake watershed management strategies. Copyright © 2017 Elsevier Ltd. All rights reserved.

Ship Detection in Optical Satellite Image Based on RX Method and PCAnet

Science.gov (United States)

Shao, Xiu; Li, Huali; Lin, Hui; Kang, Xudong; Lu, Ting

2017-12-01

In this paper, we present a novel method for ship detection in optical satellite image based on the ReedXiaoli (RX) method and the principal component analysis network (PCAnet). The proposed method consists of the following three steps. First, the spatially adjacent pixels in optical image are arranged into a vector, transforming the optical image into a 3D cube image. By taking this process, the contextual information of the spatially adjacent pixels can be integrated to magnify the discrimination between ship and background. Second, the RX anomaly detection method is adopted to preliminarily extract ship candidates from the produced 3D cube image. Finally, real ships are further confirmed among ship candidates by applying the PCAnet and the support vector machine (SVM). Specifically, the PCAnet is a simple deep learning network which is exploited to perform feature extraction, and the SVM is applied to achieve feature pooling and decision making. Experimental results demonstrate that our approach is effective in discriminating between ships and false alarms, and has a good ship detection performance.

Confirmation of Thermal Images and Vibration Signals for Intelligent Machine Fault Diagnostics

Directory of Open Access Journals (Sweden)

Achmad Widodo

2012-01-01

Full Text Available This paper deals with the maintenance technique for industrial machinery using the artificial neural network so-called self-organizing map (SOM. The aim of this work is to develop intelligent maintenance system for machinery based on an alternative way, namely, thermal images instead of vibration signals. SOM is selected due to its simplicity and is categorized as an unsupervised algorithm. Following the SOM training, machine fault diagnostics is performed by using the pattern recognition technique of machine conditions. The data used in this work are thermal images and vibration signals, which were acquired from machine fault simulator (MFS. It is a reliable tool and is able to simulate several conditions of faulty machine such as unbalance, misalignment, looseness, and rolling element bearing faults (outer race, inner race, ball, and cage defects. Data acquisition were conducted simultaneously by infrared thermography camera and vibration sensors installed in the MFS. The experimental data are presented as thermal image and vibration signal in the time domain. Feature extraction was carried out to obtain salient features sensitive to machine conditions from thermal images and vibration signals. These features are then used to train the SOM for intelligent machine diagnostics process. The results show that SOM can perform intelligent fault diagnostics with plausible accuracies.

[Application of single-band brightness variance ratio to the interference dissociation of cloud for satellite data].

Science.gov (United States)

Qu, Wei-ping; Liu, Wen-qing; Liu, Jian-guo; Lu, Yi-huai; Zhu, Jun; Qin, Min; Liu, Cheng

2006-11-01

In satellite remote-sensing detection, cloud as an interference plays a negative role in data retrieval. How to discern the cloud fields with high fidelity thus comes as a need to the following research. A new method rooting in atmospheric radiation characteristics of cloud layer, in the present paper, presents a sort of solution where single-band brightness variance ratio is used to detect the relative intensity of cloud clutter so as to delineate cloud field rapidly and exactly, and the formulae of brightness variance ratio of satellite image, image reflectance variance ratio, and brightness temperature variance ratio of thermal infrared image are also given to enable cloud elimination to produce data free from cloud interference. According to the variance of the penetrating capability for different spectra bands, an objective evaluation is done on cloud penetration of them with the factors that influence penetration effect. Finally, a multi-band data fusion task is completed using the image data of infrared penetration from cirrus nothus. Image data reconstruction is of good quality and exactitude to show the real data of visible band covered by cloud fields. Statistics indicates the consistency of waveband relativity with image data after the data fusion.

Bandwidth compression of the digitized HDTV images for transmission via satellites

Science.gov (United States)

Al-Asmari, A. KH.; Kwatra, S. C.

1992-01-01

This paper investigates a subband coding scheme to reduce the transmission bandwidth of the digitized HDTV images. The HDTV signals are decomposed into seven bands. Each band is then independently encoded. The based band is DPCM encoded and the high bands are encoded by using nonuniform Laplacian quantizers with a dead zone. By selecting the dead zone on the basis of energy in the high bands an acceptable image quality is achieved at an average of 45 Mbits/sec (Mbps) rate. This rate is comparable to some very hardware intensive schemes of transform compression or vector quantization proposed in the literature. The subband coding scheme used in this study is considered to be of medium complexity. The 45 Mbps rate is suitable for transmission of HDTV signals via satellites.

About Nano-JASMINE Satellite System and Project Status

Science.gov (United States)

Sako, Nobutada

Intelligent Space Systems Laboratory, The University of Tokyo (ISSL) and National Astronomical Observatory of Japan (NAO) have been developing a small infrared astrometry satellite named “Nano-JASMINE”. The satellite size is about 50cm cubic and 20kg, which plays a pre-cursor role of JASMINE Project which is programmed by NAO and JAXA. In addition, since there has been only one astrometry satellite HIPPARCOS by ESA in the past, Nano-JASMINE is also expected to achieve certain scientific results in the field of astrometry. In this project, ISSL aims to develop new advanced small satellite bus system whose performance is comparable to that of 100-500kg sized satellites, including attitude stability of 1 arc-second and thermal stability of the mission subsystem of 1 mK. This paper overviews the Nano-JASMINE bus system with emphasis on attitude and thermal control systems.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Katawas mineral district in Afghanistan: Chapter N in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Katawas mineral district, which has gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©AXA, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Bakhud mineral district in Afghanistan: Chapter U in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.; Davis, Philip A.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Bakhud mineral district, which has industrial fluorite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Uruzgan mineral district in Afghanistan: Chapter V in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Uruzgan mineral district, which has tin and tungsten deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2008, 2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Baghlan mineral district in Afghanistan: Chapter P in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Baghlan mineral district, which has industrial clay and gypsum deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2006, 2007, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from

Reconstruction of Missing Pixels in Satellite Images Using the Data Interpolating Empirical Orthogonal Function (DINEOF)

Science.gov (United States)

Liu, X.; Wang, M.

2016-02-01

For coastal and inland waters, complete (in spatial) and frequent satellite measurements are important in order to monitor and understand coastal biological and ecological processes and phenomena, such as diurnal variations. High-frequency images of the water diffuse attenuation coefficient at the wavelength of 490 nm (Kd(490)) derived from the Korean Geostationary Ocean Color Imager (GOCI) provide a unique opportunity to study diurnal variation of the water turbidity in coastal regions of the Bohai Sea, Yellow Sea, and East China Sea. However, there are lots of missing pixels in the original GOCI-derived Kd(490) images due to clouds and various other reasons. Data Interpolating Empirical Orthogonal Function (DINEOF) is a method to reconstruct missing data in geophysical datasets based on Empirical Orthogonal Function (EOF). In this study, the DINEOF is applied to GOCI-derived Kd(490) data in the Yangtze River mouth and the Yellow River mouth regions, the DINEOF reconstructed Kd(490) data are used to fill in the missing pixels, and the spatial patterns and temporal functions of the first three EOF modes are also used to investigate the sub-diurnal variation due to the tidal forcing. In addition, DINEOF method is also applied to the Visible Infrared Imaging Radiometer Suite (VIIRS) on board the Suomi National Polar-orbiting Partnership (SNPP) satellite to reconstruct missing pixels in the daily Kd(490) and chlorophyll-a concentration images, and some application examples in the Chesapeake Bay and the Gulf of Mexico will be presented.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Takhar mineral district in Afghanistan: Chapter Q in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Takhar mineral district, which has industrial evaporite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such

Image Mosaicking Approach for a Double-Camera System in the GaoFen2 Optical Remote Sensing Satellite Based on the Big Virtual Camera.

Science.gov (United States)

Cheng, Yufeng; Jin, Shuying; Wang, Mi; Zhu, Ying; Dong, Zhipeng

2017-06-20

The linear array push broom imaging mode is widely used for high resolution optical satellites (HROS). Using double-cameras attached by a high-rigidity support along with push broom imaging is one method to enlarge the field of view while ensuring high resolution. High accuracy image mosaicking is the key factor of the geometrical quality of complete stitched satellite imagery. This paper proposes a high accuracy image mosaicking approach based on the big virtual camera (BVC) in the double-camera system on the GaoFen2 optical remote sensing satellite (GF2). A big virtual camera can be built according to the rigorous imaging model of a single camera; then, each single image strip obtained by each TDI-CCD detector can be re-projected to the virtual detector of the big virtual camera coordinate system using forward-projection and backward-projection to obtain the corresponding single virtual image. After an on-orbit calibration and relative orientation, the complete final virtual image can be obtained by stitching the single virtual images together based on their coordinate information on the big virtual detector image plane. The paper subtly uses the concept of the big virtual camera to obtain a stitched image and the corresponding high accuracy rational function model (RFM) for concurrent post processing. Experiments verified that the proposed method can achieve seamless mosaicking while maintaining the geometric accuracy.

Detecting Weather Radar Clutter by Information Fusion With Satellite Images and Numerical Weather Prediction Model Output

DEFF Research Database (Denmark)

Bøvith, Thomas; Nielsen, Allan Aasbjerg; Hansen, Lars Kai

2006-01-01

A method for detecting clutter in weather radar images by information fusion is presented. Radar data, satellite images, and output from a numerical weather prediction model are combined and the radar echoes are classified using supervised classification. The presented method uses indirect...... information on precipitation in the atmosphere from Meteosat-8 multispectral images and near-surface temperature estimates from the DMI-HIRLAM-S05 numerical weather prediction model. Alternatively, an operational nowcasting product called 'Precipitating Clouds' based on Meteosat-8 input is used. A scale...

Space Solar Power Satellite Systems, Modern Small Satellites, and Space Rectenna

Science.gov (United States)

Bergsrud, Corey Alexis Marvin

Space solar power satellite (SSPS) systems is the concept of placing large satellite into geostationary Earth orbit (GEO) to harvest and convert massive amounts of solar energy into microwave energy, and to transmit the microwaves to a rectifying antenna (rectenna) array on Earth. The rectenna array captures and converts the microwave power into usable power that is injected into the terrestrial electric grid for use. This work approached the microwave power beam as an additional source of power (with solar) for lower orbiting satellites. Assuming the concept of retrodirectivity, a GEO-SSPS antenna array system tracks and delivers microwave power to lower orbiting satellites. The lower orbiting satellites are equipped with a stacked photovoltaic (PV)/rectenna array hybrid power generation unit (HPGU) in order to harvest solar and/or microwave energy for on-board use during orbit. The area, and mass of the PV array part of the HPGU was reduced at about 32% beginning-of-life power in order to achieve the spacecraft power requirements. The HPGU proved to offer a mass decrease in the PGU, and an increase in mission life due to longer living component life of the rectenna array. Moreover, greater mission flexibility is achieved through a track and power delivery concept. To validate the potential advantages offered by a HPGU, a mission concept was presented that utilizes modern small satellites as technology demonstrators. During launch, a smaller power receiving "daughter" satellite sits inside a larger power transmitting "mother" satellite. Once separated from the launch vehicle the daughter satellite is ejected away from the mother satellite, and each satellite deploys its respective power transmitting or power receiving hardware's for experimentation. The concept of close proximity mission operations between the satellites is considered. To validate the technology of the space rectenna array part of the HPGU, six milestones were completed in the design. The first

Weather Satellite Pictures and How to Obtain Them.

Science.gov (United States)

Petit, Noel J.; Johnson, Philip

1982-01-01

An introduction to satellite meteorology is presented to promote use of live weather satellite photographs in the classroom. Topics addressed include weather satellites, how they work, earth emissions, satellite photography, satellite image analysis, obtaining satellite pictures, and future considerations. Includes sources for materials to…

Lock-in thermal imaging for the early-stage detection of cutaneous melanoma: a feasibility study.

Science.gov (United States)

Bonmarin, Mathias; Le Gal, Frédérique-Anne

2014-04-01

This paper theoretically evaluates lock-in thermal imaging for the early-stage detection of cutaneous melanoma. Lock-in thermal imaging is based on the periodic thermal excitation of the specimen under test. Resulting surface temperature oscillations are recorded with an infrared camera and allow the detection of variations of the sample's thermophysical properties under the surface. In this paper, the steady-state and transient skin surface temperatures are numerically derived for a different stage of development of the melanoma lesion using a two-dimensional axisymmetric multilayer heat-transfer model. The transient skin surface temperature signals are demodulated according to the digital lock-in principle to compute both a phase and an amplitude image of the lesions. The phase image can be advantageously used to accurately detect cutaneous melanoma at an early stage of development while the maximal phase shift can give precious information about the lesion invasion depth. The ability of lock-in thermal imaging to suppress disturbing subcutaneous thermal signals is demonstrated. The method is compared with the previously proposed pulse-based approaches, and the influence of the modulation frequency is further discussed. Copyright © 2014 Elsevier Ltd. All rights reserved.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Haji-Gak mineral district in Afghanistan: Chapter C in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Haji-Gak mineral district, which has iron ore deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA,2006,2007), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kharnak-Kanjar mineral district in Afghanistan: Chapter K in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Kharnak-Kanjar mineral district, which has mercury deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008,2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Dusar-Shaida mineral district in Afghanistan: Chapter I in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Dusar-Shaida mineral district, which has copper and tin deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the

THERMAL EFFECTS ON CAMERA FOCAL LENGTH IN MESSENGER STAR CALIBRATION AND ORBITAL IMAGING

Directory of Open Access Journals (Sweden)

S. Burmeister

2018-04-01

Full Text Available We analyse images taken by the MErcury Surface, Space ENviorment, GEochemistry, and Ranging (MESSENGER spacecraft for the camera’s thermal response in the harsh thermal environment near Mercury. Specifically, we study thermally induced variations in focal length of the Mercury Dual Imaging System (MDIS. Within the several hundreds of images of star fields, the Wide Angle Camera (WAC typically captures up to 250 stars in one frame of the panchromatic channel. We measure star positions and relate these to the known star coordinates taken from the Tycho-2 catalogue. We solve for camera pointing, the focal length parameter and two non-symmetrical distortion parameters for each image. Using data from the temperature sensors on the camera focal plane we model a linear focal length function in the form of f(T = A0 + A1 T. Next, we use images from MESSENGER’s orbital mapping mission. We deal with large image blocks, typically used for the production of a high-resolution digital terrain models (DTM. We analyzed images from the combined quadrangles H03 and H07, a selected region, covered by approx. 10,600 images, in which we identified about 83,900 tiepoints. Using bundle block adjustments, we solved for the unknown coordinates of the control points, the pointing of the camera – as well as the camera’s focal length. We then fit the above linear function with respect to the focal plane temperature. As a result, we find a complex response of the camera to thermal conditions of the spacecraft. To first order, we see a linear increase by approx. 0.0107 mm per degree temperature for the Narrow-Angle Camera (NAC. This is in agreement with the observed thermal response seen in images of the panchromatic channel of the WAC. Unfortunately, further comparisons of results from the two methods, both of which use different portions of the available image data, are limited. If leaving uncorrected, these effects may pose significant difficulties in

High resolution satellite image indexing and retrieval using SURF features and bag of visual words

Science.gov (United States)

Bouteldja, Samia; Kourgli, Assia

2017-03-01

In this paper, we evaluate the performance of SURF descriptor for high resolution satellite imagery (HRSI) retrieval through a BoVW model on a land-use/land-cover (LULC) dataset. Local feature approaches such as SIFT and SURF descriptors can deal with a large variation of scale, rotation and illumination of the images, providing, therefore, a better discriminative power and retrieval efficiency than global features, especially for HRSI which contain a great range of objects and spatial patterns. Moreover, we combine SURF and color features to improve the retrieval accuracy, and we propose to learn a category-specific dictionary for each image category which results in a more discriminative image representation and boosts the image retrieval performance.

Mapping soil heterogeneity using RapidEye satellite images

Science.gov (United States)

Piccard, Isabelle; Eerens, Herman; Dong, Qinghan; Gobin, Anne; Goffart, Jean-Pierre; Curnel, Yannick; Planchon, Viviane

2016-04-01

In the frame of BELCAM, a project funded by the Belgian Science Policy Office (BELSPO), researchers from UCL, ULg, CRA-W and VITO aim to set up a collaborative system to develop and deliver relevant information for agricultural monitoring in Belgium. The main objective is to develop remote sensing methods and processing chains able to ingest crowd sourcing data, provided by farmers or associated partners, and to deliver in return relevant and up-to-date information for crop monitoring at the field and district level based on Sentinel-1 and -2 satellite imagery. One of the developments within BELCAM concerns an automatic procedure to detect soil heterogeneity within a parcel using optical high resolution images. Such heterogeneity maps can be used to adjust farming practices according to the detected heterogeneity. This heterogeneity may for instance be caused by differences in mineral composition of the soil, organic matter content, soil moisture or soil texture. Local differences in plant growth may be indicative for differences in soil characteristics. As such remote sensing derived vegetation indices may be used to reveal soil heterogeneity. VITO started to delineate homogeneous zones within parcels by analyzing a series of RapidEye images acquired in 2015 (as a precursor for Sentinel-2). Both unsupervised classification (ISODATA, K-means) and segmentation techniques were tested. Heterogeneity maps were generated from images acquired at different moments during the season (13 May, 30 June, 17 July, 31 August, 11 September and 1 November 2015). Tests were performed using blue, green, red, red edge and NIR reflectances separately and using derived indices such as NDVI, fAPAR, CIrededge, NDRE2. The results for selected winter wheat, maize and potato fields were evaluated together with experts from the collaborating agricultural research centers. For a few fields UAV images and/or yield measurements were available for comparison.

REVIEW OF METHODS FOR THE SURVEILLANCE AND ACCESS CONTROL USING THE THERMAL IMAGING SYSTEM

Directory of Open Access Journals (Sweden)

Mate Krišto

2016-12-01

Full Text Available This paper presents methods for human detection for application in the field of national security in the context of state border surveillance. Except in the context of state border security, the presented methods can be applied to monitor other protected object and infrastructure such as ports and airports, power plants, water supply systems, oil pipelines, etc. Presented methods are based on use of thermal imaging systems for the human detection, recognition and identification. In addition to methods for the detection of persons, are presented and methods for face recognition and identification of the person. The use of such systems has special significance in the context of national security in the domain of timely detection of illegal crossing of state border or illegal movement near buildings, which are of special importance for national security such as traffic infrastructure facilities, power plants, military bases, especially in mountain or forests areas. In this context, thermal imaging has significant advantages over the optical camera surveillance systems because thermal imaging is robust to weather conditions and due to such an infrared thermal system can successfully applied in any weather conditions, or the periods of the day. Featured are procedures that has human detection results as well as a brief survey of specific implementation in terms of the use of infrared thermal imagers mounted on autonomous vehicles (AV and unmanned aerial vehicles (UAV. In addition to the above in this paper are described techniques and methods of face detection and human identification based on thermal image (thermogram.

Analysis and Assessment of Land Use Change in Alexandria, Egypt Using Satellite Images, GIS, and Modelling Techniques

International Nuclear Information System (INIS)

Abdou Azaz, L.K.

2008-01-01

Alexandria is the second largest urban governorate in Egypt and has seen significant urban growth in its modern and contemporary history. This study investigates the urban growth phenomenon in Alexandria, Egypt, using the integration of remote sensing and GIS. The urban physical expansion and change were detected using Landsat satellite images. The satellite images of years 1984 and 1993 were first geo referenced, achieving a very small RMSE that provided high accuracy data for satellite image analysis. Then, the images were classified using a tailored classification scheme with accuracy of 93.82% and 95.27% for 1984 and 1993 images respectively. This high accuracy enabled detecting land use/land cover changes with high confidence using a post-classification comparison method. One of the most important findings here is the loss of cultivated land in favour of urban expansion. If the current loss rates continued, 75% of green lands would be lost by year 2191. These hazardous rates call for an urban growth management policy that can preserve such valuable resources to achieve sustainable urban development. Modelling techniques can help in defining the scenarios of urban growth. In this study, the SLEUTH urban growth model was applied to predict future urban expansion in Alexandria until the year 2055. The application of this model in Alexandria of Egypt with its different environmental characteristics is the first application outside USA and Europe. The results revealed that future urban growth would continue along the edges of the current urban extent. This means that the cultivated lands in the east and the southeast of the city will be decreased. To deal with such crisis, there is a serious need for a comprehensive urban growth management programme that can be based on the best practices in similar situations

MR imaging and histopathologic correlations of thermal injuries induced by interstitial laser applications

International Nuclear Information System (INIS)

Anzai, Y.; Lufkin, R.B.; Castro, D.J.; Farahani, K.; Chen, H.W.; Hirchowiz, S.

1991-01-01

Interstitial laser phototherapy for deep-seated tumors may become an attractive therapeutic modality when a noninvasive, accurate monitoring system is developed. In this paper, to devaluate the ability of MR imaging to differentiate reversible and irreversible thermal injuries induced by laser therapy, the precise correlation of MR and histopathologic findings are investigated in the in vivo model. Nd:YAG lasers were applied to normal musculature of rabbits, and MR examinations were performed immediately after laser exposure and followed up for up to 10 weeks. The sequential MR images were correlated with histopathologic findings. T2-weighted MR imaging clearly showed laser-induced thermal injuries on any postoperative day. MR imaging of acute thermal injuries showed a central cavity, low-signal zone of coagulative necrosis and a peripheral high-signal layer of interstitial edema. The infiltration of neutrophils followed by fibrovascular response was identified on the marginal edema layer after 6 postoperative days

Comparison of Hyperspectral and Multispectral Satellites for Discriminating Land Cover in Northern California

Science.gov (United States)

Clark, M. L.; Kilham, N. E.

2015-12-01

Land-cover maps are important science products needed for natural resource and ecosystem service management, biodiversity conservation planning, and assessing human-induced and natural drivers of land change. Most land-cover maps at regional to global scales are produced with remote sensing techniques applied to multispectral satellite imagery with 30-500 m pixel sizes (e.g., Landsat, MODIS). Hyperspectral, or imaging spectrometer, imagery measuring the visible to shortwave infrared regions (VSWIR) of the spectrum have shown impressive capacity to map plant species and coarser land-cover associations, yet techniques have not been widely tested at regional and greater spatial scales. The Hyperspectral Infrared Imager (HyspIRI) mission is a VSWIR hyperspectral and thermal satellite being considered for development by NASA. The goal of this study was to assess multi-temporal, HyspIRI-like satellite imagery for improved land cover mapping relative to multispectral satellites. We mapped FAO Land Cover Classification System (LCCS) classes over 22,500 km2 in the San Francisco Bay Area, California using 30-m HyspIRI, Landsat 8 and Sentinel-2 imagery simulated from data acquired by NASA's AVIRIS airborne sensor. Random Forests (RF) and Multiple-Endmember Spectral Mixture Analysis (MESMA) classifiers were applied to the simulated images and accuracies were compared to those from real Landsat 8 images. The RF classifier was superior to MESMA, and multi-temporal data yielded higher accuracy than summer-only data. With RF, hyperspectral data had overall accuracy of 72.2% and 85.1% with full 20-class and reduced 12-class schemes, respectively. Multispectral imagery had lower accuracy. For example, simulated and real Landsat data had 7.5% and 4.6% lower accuracy than HyspIRI data with 12 classes, respectively. In summary, our results indicate increased mapping accuracy using HyspIRI multi-temporal imagery, particularly in discriminating different natural vegetation types, such as

From OLS to VIIRS, an overview of nighttime satellite aerosol retrievals using artificial light sources

Science.gov (United States)

Zhang, J.; Miller, S. D.; Reid, J. S.; Hyer, E. J.; McHardy, T. M.

2015-12-01

Compared to abundant daytime satellite-based observations of atmospheric aerosol, observations at night are relatively scarce. In particular, conventional satellite passive imaging radiometers, which offer expansive swaths of spatial coverage compared to non-scanning lidar systems, lack sensitivity to most aerosol types via the available thermal infrared bands available at night. In this talk, we make the fundamental case for the importance of nighttime aerosol information in forecast models, and the need to mitigate the existing nocturnal gap. We review early attempts at estimating nighttime aerosol optical properties using the modulation of stable artificial surface lights. Initial algorithm development using DMSP Operational Linescan System (OLS) has graduated to refined techniques based on the Suomi-NPP Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB). We present examples of these retrievals for selected cases and compare the results to available surface-based point-source validation data.

Remotely Characterizing the Topographic and Thermal Evolution of Kīlauea's Lava Flow Field

Science.gov (United States)

Rumpf, M. E.; Vaughan, R. G.; Poland, M. P.

2017-12-01

New technologies in satellite data acquisition and the continuous development of analysis software capabilities are greatly improving the ability of scientists to monitor volcanoes in near-real-time. Satellite-based thermal infrared (TIR) data are used to monitor and analyze new and ongoing volcanic activity by identifying and quantifying surface thermal characteristics and lava flow discharge rates. Improved detector sensitivities provide unprecedented spatial detail in visible to shortwave infrared (VSWIR) satellite imagery. The acquisition of stereo and tri-stereo visible imagery, as well as SAR, by an increasing number of satellite systems enables the creation of digital elevation models (DEMs) at higher temporal frequencies and resolutions than in the past. Free, user-friendly software programs, such as NASA's Ames Stereo Pipeline and Google Earth Engine, ease the accessibility and usability of satellite data to users unfamiliar with traditional analysis techniques. An effective and efficient integration of these technologies can be utilized towards volcano monitoring.Here, we use the active lava flows from the East Rift Zone vents of Kīlauea Volcano, Hawai`i as a testing ground for developing new techniques in multi-sensor volcano remote sensing. We use DEMs generated from stereo and tri-stereo images captured by the WorldView3 and Pleiades satellite systems to assess topographic changes over time at the active flow fields. Time-series data of lava flow area, thickness, and discharge rate developed from thermal emission measurements collected by ASTER, Landsat 8, and WorldView3 are compared to satellite-detected topographic changes and to ground observations of flow development to identify behavioral patterns and to monitor flow field evolution. We explore methods of combining these visual and TIR data sets collected by multiple satellite systems with a variety of resolutions and repeat times. Our ultimate goal is to develop integrative tools for near

Dsm Based Orientation of Large Stereo Satellite Image Blocks

Science.gov (United States)

d'Angelo, P.; Reinartz, P.

2012-07-01

High resolution stereo satellite imagery is well suited for the creation of digital surface models (DSM). A system for highly automated and operational DSM and orthoimage generation based on CARTOSAT-1 imagery is presented, with emphasis on fully automated georeferencing. The proposed system processes level-1 stereo scenes using the rational polynomial coefficients (RPC) universal sensor model. The RPC are derived from orbit and attitude information and have a much lower accuracy than the ground resolution of approximately 2.5 m. In order to use the images for orthorectification or DSM generation, an affine RPC correction is required. In this paper, GCP are automatically derived from lower resolution reference datasets (Landsat ETM+ Geocover and SRTM DSM). The traditional method of collecting the lateral position from a reference image and interpolating the corresponding height from the DEM ignores the higher lateral accuracy of the SRTM dataset. Our method avoids this drawback by using a RPC correction based on DSM alignment, resulting in improved geolocation of both DSM and ortho images. Scene based method and a bundle block adjustment based correction are developed and evaluated for a test site covering the nothern part of Italy, for which 405 Cartosat-1 Stereopairs are available. Both methods are tested against independent ground truth. Checks against this ground truth indicate a lateral error of 10 meters.

Combining a thermal-imaging diagnostic with an existing imaging VISAR diagnostic at the National Ignition Facility (NIF)

International Nuclear Information System (INIS)

Robert M, Malone; John R, Celesteb; Peter M, Celliers; Brent C, Froggeta; Robert L, Guyton; Morris I, Kaufman; Tony L, Lee; Brian J, MacGowan; Edmund W, Ng; Imants P, Reinbachs; Ronald B, Robinson; Lynn G, Seppala; Tom W, Tunnell; Phillip W, Watts

2005-01-01

Optical diagnostics are currently being designed to analyze high-energy density physics experiments at the National Ignition Facility (NIF). Two independent line-imaging Velocity Interferometer System for Any Reflector (VISAR) interferometers have been fielded to measure shock velocities, breakout times, and emission of targets having sizes of 1-5 mm. An 8-inch-diameter, fused silica triplet lens collects light at f/3 inside the 30-foot-diameter NIF vacuum chamber. VISAR recordings use a 659.5-nm probe laser. By adding a specially coated beam splitter to the interferometer table, light at wavelengths from 540 to 645 nm is spilt into a thermal-imaging diagnostic. Because fused silica lenses are used in the first triplet relay, the intermediate image planes for different wavelengths separate by considerable distances. A corrector lens on the interferometer table reunites these separated wavelength planes to provide a good image. Thermal imaging collects light at f/5 from a 2-mm object placed at Target Chamber Center (TCC). Streak cameras perform VISAR and thermal-imaging recording. All optical lenses are on kinematic mounts so that pointing accuracy of the optical axis may be checked. Counter-propagating laser beams (orange and red) are used to align both diagnostics. The red alignment laser is selected to be at the 50 percent reflection point of the beam splitter. This alignment laser is introduced at the recording streak cameras for both diagnostics and passes through this special beam splitter on its way into the NIF vacuum chamber

Space Solar Power: Satellite Concepts

Science.gov (United States)

Little, Frank E.

1999-01-01

Space Solar Power (SSP) applies broadly to the use of solar power for space related applications. The thrust of the NASA SSP initiative is to develop concepts and demonstrate technology for applying space solar power to NASA missions. Providing power from satellites in space via wireless transmission to a receiving station either on earth, another celestial body or a second satellite is one goal of the SSP initiative. The sandwich design is a satellite design in which the microwave transmitting array is the front face of a thin disk and the back of the disk is populated with solar cells, with the microwave electronics in between. The transmitter remains aimed at the earth in geostationary orbit while a system of mirrors directs sunlight to the photovoltaic cells, regardless of the satellite's orientation to the sun. The primary advantage of the sandwich design is it eliminates the need for a massive and complex electric power management and distribution system for the satellite. However, it requires a complex system for focusing sunlight onto the photovoltaic cells. In addition, positioning the photovoltaic array directly behind the transmitting array power conversion electronics will create a thermal management challenge. This project focused on developing designs and finding emerging technology to meet the challenges of solar tracking, a concentrating mirror system including materials and coatings, improved photovoltaic materials and thermal management.

Problems of thermal IR-imaging in evaluation of burn wounds

International Nuclear Information System (INIS)

Nowakowski, A.

2009-01-01

Results of the research devoted to application of thermal IR-imaging in diagnostics of burn wounds are discussed. The main aim of the work was to develop an effective method for quantitative evaluation of the depth of a burn wound and for classification of regions for surgical treatment. The criterion of determination the area of the wound to be treated surgically is the time, which should not exceed three weeks for natural healing of a burn wound. Prediction that the healing process may last longer is concluded by immediate surgical intervention. We concentrate on using for this purpose QIRT - NDT TI methods (Quantitative Infra-Red Thermography - Non-Destructive Testing Thermal Imaging); especially - active dynamic thermography - ADT. In this work both, classical thermography using a high quality thermal camera as well as ADT are applied and the results of analysis are joined, allowing multimodality diagnostic approach and improved classification of burns requiring surgical treatment. Now our work in application of thermal imaging in determination of burns is continued for around 10 years, as the first publication showing our methodology was presented in 1999. In 2001, during the Thermosense conference, we have been awarded the Andronicos Kantsios Award for the work on Medical applications of model based dynamic thermography. Important reports of our experience in classical as well as ADT thermography are already published. Now we concentrate on practical aspects of the problem, trying to construct a measuring set to be operative even by not experienced staff and meeting all of necessary requirements for clinical applications. (author)

Quantitative analysis of geomorphic processes using satellite image data at different scales

Science.gov (United States)

Williams, R. S., Jr.

1985-01-01

When aerial and satellite photographs and images are used in the quantitative analysis of geomorphic processes, either through direct observation of active processes or by analysis of landforms resulting from inferred active or dormant processes, a number of limitations in the use of such data must be considered. Active geomorphic processes work at different scales and rates. Therefore, the capability of imaging an active or dormant process depends primarily on the scale of the process and the spatial-resolution characteristic of the imaging system. Scale is an important factor in recording continuous and discontinuous active geomorphic processes, because what is not recorded will not be considered or even suspected in the analysis of orbital images. If the geomorphic process of landform change caused by the process is less than 200 m in x to y dimension, then it will not be recorded. Although the scale factor is critical, in the recording of discontinuous active geomorphic processes, the repeat interval of orbital-image acquisition of a planetary surface also is a consideration in order to capture a recurring short-lived geomorphic process or to record changes caused by either a continuous or a discontinuous geomorphic process.

Handbook of satellite applications

CERN Document Server

Madry, Scott; Camacho-Lara, Sergio

2013-01-01

Top space experts from around the world have collaborated to produce this comprehensive, authoritative, and clearly illustrated reference guide to the fast growing, multi-billion dollar field of satellite applications and space communications. This handbook, done under the auspices of the International Space University based in France, addresses not only system technologies but also examines market dynamics, technical standards and regulatory constraints. The handbook is a completely multi-disciplinary reference book that covers, in an in-depth fashion, the fields of satellite telecommunications, Earth observation, remote sensing, satellite navigation, geographical information systems, and geosynchronous meteorological systems. It covers current practices and designs as well as advanced concepts and future systems. It provides a comparative analysis of the common technologies and design elements for satellite application bus structures, thermal controls, power systems, stabilization techniques, telemetry, com...

Automatic Centerline Extraction of Coverd Roads by Surrounding Objects from High Resolution Satellite Images

Science.gov (United States)

Kamangir, H.; Momeni, M.; Satari, M.

2017-09-01

This paper presents an automatic method to extract road centerline networks from high and very high resolution satellite images. The present paper addresses the automated extraction roads covered with multiple natural and artificial objects such as trees, vehicles and either shadows of buildings or trees. In order to have a precise road extraction, this method implements three stages including: classification of images based on maximum likelihood algorithm to categorize images into interested classes, modification process on classified images by connected component and morphological operators to extract pixels of desired objects by removing undesirable pixels of each class, and finally line extraction based on RANSAC algorithm. In order to evaluate performance of the proposed method, the generated results are compared with ground truth road map as a reference. The evaluation performance of the proposed method using representative test images show completeness values ranging between 77% and 93%.

Use of high resolution satellite images for tracking of changes in the lineament structure, caused by earthquakes

OpenAIRE

Arellano-Baeza, A. A.; Garcia, R. V.; Trejo-Soto, M.

2007-01-01

Over the last decades strong efforts have been made to apply new spaceborn technologies to the study and possible forecast of strong earthquakes. In this study we use ASTER/TERRA multispectral satellite images for detection and analysis of changes in the system of lineaments previous to a strong earthquake. A lineament is a straight or a somewhat curved feature in an image, which it is possible to detect by a special processing of images based on directional filtering and or Hough transform. ...

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kandahar mineral district in Afghanistan: Chapter Z in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Kandahar mineral district, which has bauxite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA,2006,2007,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Farah mineral district in Afghanistan: Chapter FF in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.

2014-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Farah mineral district, which has spectral reflectance anomalies indicative of copper, zinc, lead, silver, and gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA, 2007, 2008, 2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Zarkashan mineral district in Afghanistan: Chapter G in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Zarkashan mineral district, which has copper and gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Khanneshin mineral district in Afghanistan: Chapter A in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Khanneshin mineral district, which has uranium, thorium, rare-earth-element, and apatite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008,2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Nalbandon mineral district in Afghanistan: Chapter L in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Nalbandon mineral district, which has lead and zinc deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2007, 2008, 2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Balkhab mineral district in Afghanistan: Chapter B in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Balkhab mineral district, which has copper deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match

Discriminating satellite IR anomalies associated with the MS 7.1 Yushu earthquake in China

Science.gov (United States)

Qin, Kai; Wu, Lixin; Zheng, Shuo; Ma, Weiyu

2018-03-01

In the process of exploring pre-earthquake thermal anomalies using satellite infrared data, Blackett et al. (2011) found that the previously reported anomalies before the 2001 Mw 7.7 Gujarat earthquake, in India, were related to positive biases caused by data gaps due to cloud cover and mosaicing of neighboring orbits of MODIS satellite data. They supposed that such effects could also be responsible for other cases. We noted a strip-shaped TIR anomaly on March 17th, 2010, 28 days before the Ms. 7.1 Yushu earthquake (Qin et al., 2011). Here we again investigate multi-year infrared satellite data in different bands to discriminate whether the anomaly is associated with the earthquake, or is only bias caused by the data gaps. From the water vapor images, we find lots of clouds that have TIR anomalies. However, on the cloudiness background, there is an obvious strip-shaped gap matching the tectonic faults almost perfectly. In particular, the animation loops of hourly water vapor images show that the cloud kept moving from west to east, while they never covered the strip-shaped gap. We consider that the cloud with this special spatial pattern should have implied the abnormal signals associated with the seismogenic process. Based on current physical models, the satellite IR anomalies both on TIR and water vapor bands can qualitatively be explained using synthetic mechanisms.

Mapping Impervious Surface Expansion using Medium-resolution Satellite Image Time Series: A Case Study in the Yangtze River Delta, China

Science.gov (United States)

Gao, Feng; DeColstoun, Eric Brown; Ma, Ronghua; Weng, Qihao; Masek, Jeffrey G.; Chen, Jin; Pan, Yaozhong; Song, Conghe

2012-01-01

Cities have been expanding rapidly worldwide, especially over the past few decades. Mapping the dynamic expansion of impervious surface in both space and time is essential for an improved understanding of the urbanization process, land-cover and land-use change, and their impacts on the environment. Landsat and other medium-resolution satellites provide the necessary spatial details and temporal frequency for mapping impervious surface expansion over the past four decades. Since the US Geological Survey opened the historical record of the Landsat image archive for free access in 2008, the decades-old bottleneck of data limitation has gone. Remote-sensing scientists are now rich with data, and the challenge is how to make best use of this precious resource. In this article, we develop an efficient algorithm to map the continuous expansion of impervious surface using a time series of four decades of medium-resolution satellite images. The algorithm is based on a supervised classification of the time-series image stack using a decision tree. Each imerpervious class represents urbanization starting in a different image. The algorithm also allows us to remove inconsistent training samples because impervious expansion is not reversible during the study period. The objective is to extract a time series of complete and consistent impervious surface maps from a corresponding times series of images collected from multiple sensors, and with a minimal amount of image preprocessing effort. The approach was tested in the lower Yangtze River Delta region, one of the fastest urban growth areas in China. Results from nearly four decades of medium-resolution satellite data from the Landsat Multispectral Scanner (MSS), Thematic Mapper (TM), Enhanced Thematic Mapper plus (ETM+) and China-Brazil Earth Resources Satellite (CBERS) show a consistent urbanization process that is consistent with economic development plans and policies. The time-series impervious spatial extent maps derived

Thermal imaging as a smartphone application: exploring and implementing a new concept

Science.gov (United States)

Yanai, Omer

2014-06-01

Today's world is going mobile. Smartphone devices have become an important part of everyday life for billions of people around the globe. Thermal imaging cameras have been around for half a century and are now making their way into our daily lives. Originally built for military applications, thermal cameras are starting to be considered for personal use, enabling enhanced vision and temperature mapping for different groups of professional individuals. Through a revolutionary concept that turns smartphones into fully functional thermal cameras, we have explored how these two worlds can converge by utilizing the best of each technology. We will present the thought process, design considerations and outcome of our development process, resulting in a low-power, high resolution, lightweight USB thermal imaging device that turns Android smartphones into thermal cameras. We will discuss the technological challenges that we faced during the development of the product, and what are the system design decisions taken during the implementation. We will provide some insights we came across during this development process. Finally, we will discuss the opportunities that this innovative technology brings to the market.

Primena satelitskih snimaka za dopunu sadržaja topografskih karata / An application of satellite images for improving the content of topographic maps